{"as_of":"2026-08-18T19:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7be7f031e23d66d5ef72041ff07c6b3186b8df55360bc01de4a515b180926d41","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T14:06:41.671721Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:53:57.377120Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-14T02:23:37.887104Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.15695","snapshot_observed_at":"2026-08-07T04:53:57.377120Z","title":"Contextual knowledge sharing in multi-agent reinforcement learning with decentralized communi- cation and coordination.arXiv preprint arXiv:2501.15695, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09335","last_updated":"2025-06-11T02:28:05Z","snapshot_observed_at":"2026-08-12T06:24:00.342180Z","submitted_at":"2025-06-11T02:28:05Z","title":"Intelligent System of Emergent Knowledge: A Coordination Fabric for Billions of Minds","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T04:53:57.377120Z"},"links":{"cited_paper":"/paper/2501.15695","citing_paper":"/paper/2506.09335"},"observation_digest":"sha256:c5166126e964f4dfc270d02fa02f3b0a670379e27171c7a1ca1da5281f01c929","observation_id":"14d0111c-ad84-4196-a7eb-aa75308b9a03","resolution":{"observed_at":"2026-08-07T04:53:57.377120Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"cited_work":{"arxiv_id":"2501.15695","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.15695","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Contextual knowledge sharing in multi-agent reinforcement learning with decentralized communication and coordination","venue":null,"work_id":"8ad3eb0f-80e0-4a05-99ca-8ca4859f547d","year":2025},"citing_paper":{"arxiv_id":"2605.13172","last_updated":"2026-05-13T08:33:28Z","snapshot_observed_at":"2026-08-11T11:19:02.330631Z","submitted_at":"2026-05-13T08:33:28Z","title":"When Does Hierarchy Help? Benchmarking Agent Coordination in Event-Driven Industrial Scheduling","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-14T02:19:10.912487Z"},"links":{"cited_paper":"/paper/2501.15695","citing_paper":"/paper/2605.13172"},"observation_digest":"sha256:901f8e493601f2a3cbe29b787ef58bfbca801cbb25d317bc114fbebc7a6598a2","observation_id":"926d0e52-fde8-4fc4-aa93-d177f1b02665","resolution":{"observed_at":"2026-05-14T02:23:37.891272Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.15695/citation-record","integrity":"/paper/2501.15695/integrity","json":"/paper/2501.15695/citation-record.json","paper":"/paper/2501.15695"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.01968","last_updated":"2025-01-29T05:41:52Z","snapshot_observed_at":"2026-08-16T14:21:57.695579Z","submitted_at":"2024-02-03T00:27:22Z","title":"A Survey on Context-Aware Multi-Agent Systems: Techniques, Challenges and Future Directions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01968","snapshot_observed_at":"2026-08-10T14:06:41.544178Z","title":"A survey on context- aware multi-agent systems: Techniques, challenges and future direc- tions,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.544178Z"},"links":{"cited_paper":"/paper/2402.01968","citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:707648d42f83074104d98d83213f3677d9fa53dbd0da040fda8e4bdbb81e7da1","observation_id":"bbacc4c8-3289-4d92-8848-b65b7162f30a","resolution":{"observed_at":"2026-08-10T14:06:41.544178Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.115412Z","title":"Survey of multi-agent systems for microgrid control,","venue":null,"work_id":"94067e99-3ae4-4e27-9c93-23f5e3d3cc15","year":2015},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.548150Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:fd93a638d6842d4f0f3eb94126304ba61c30a154f70c0f37a091ff4ce96f1ac1","observation_id":"0e803ff3-56e4-4318-a453-1809c8e959a2","resolution":{"observed_at":"2026-08-10T14:06:42.119067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.104307Z","title":"Survey of agent-based cloud computing applications,","venue":null,"work_id":"c0fae829-d333-429d-9163-3c9e64ff10f4","year":2019},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.551284Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:6db5589d782e071fea59a939df9effb4f24e8434595c152f89c95a41b67d6222","observation_id":"803821ca-3b9f-403d-9153-e67e2c7c5d84","resolution":{"observed_at":"2026-08-10T14:06:42.107897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.554299Z","title":"Consensus in multi-agent systems: a review,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.554299Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:1d8aa1bc733336f999715a9fcd3e75349ce1c5cc6b449318462396235b4ed29d","observation_id":"a8c22b42-1887-4d16-b39b-1c40fa42fa78","resolution":{"observed_at":"2026-08-10T14:06:41.554299Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.087042Z","title":"Multi-agent deep reinforcement learning: a survey,","venue":null,"work_id":"9babed16-0627-40e7-be03-0365cff88459","year":2022},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.557563Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:062bdc3de0e7f40dbb6dd2843e4de481deda94c0da5cd82dbc415e01e2154638","observation_id":"fd0154fb-7460-4921-bf55-14f710c78d13","resolution":{"observed_at":"2026-08-10T14:06:42.090553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.077081Z","title":"Multi-agent reinforcement learning as a rehearsal for decentralized planning,","venue":null,"work_id":"2367ed16-944e-4d3e-a6c5-e96c44d65817","year":2016},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.560432Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:cd7eb8920b2f866b825ba6be29d0e251afaac00e26a0c2ac138b9403cf22b331","observation_id":"7425d78a-a90d-493f-86fd-fb20cdb6606d","resolution":{"observed_at":"2026-08-10T14:06:42.080460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.067570Z","title":"Cooperative multi-agent control using deep reinforcement learning,","venue":null,"work_id":"3dc0963c-aebb-478e-8575-1263696b64df","year":2017},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.563579Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:fc56ddef7180540d8472ffca993f66490615d660663aba2546d3bb7315aa0158","observation_id":"8f09cfe1-2baa-464b-ad6f-ffa48a3a6904","resolution":{"observed_at":"2026-08-10T14:06:42.070628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.566129Z","title":"Multi-agent actor-critic for mixed cooperative-competitive environ- ments,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.566129Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:5a2ffcdce1b918e91fc1f08ebb592bef26cbd1a76f219a3cf8ae7913e6952a83","observation_id":"c76a81d2-f5d5-4615-97bd-63aa61e18779","resolution":{"observed_at":"2026-08-10T14:06:41.566129Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.568962Z","title":"Counterfactual multi-agent policy gradients,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.568962Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:55825b13188869b0c10a6fbb9f0129f2ae7cf51d31db9567f51221e10446f97f","observation_id":"b01f5bca-a967-4378-bfa6-b9abd84574bc","resolution":{"observed_at":"2026-08-10T14:06:41.568962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.044864Z","title":"Shapley q-value: A local reward approach to solve global reward games,","venue":null,"work_id":"eaa094a8-fd89-499d-8161-78c3c51ede21","year":2020},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.571735Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:ef56dfc44898231d52ec27eb308202b540c7ff19ccc6eb072ddcade0583e200e","observation_id":"2e643496-73e2-469d-b1a4-c96ee534a1af","resolution":{"observed_at":"2026-08-10T14:06:42.047902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.574297Z","title":"Monotonic value function factorisation for deep multi- agent reinforcement learning,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.574297Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:1221075b31292a866a247a835e0960519208661de51b863048a3f941398278e9","observation_id":"aaaf07fe-95fa-4607-a36c-c9a4b7638c57","resolution":{"observed_at":"2026-08-10T14:06:41.574297Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.029319Z","title":"Roma: Multi-agent reinforcement learning with emergent roles,","venue":null,"work_id":"1d5444e4-30a9-4f67-a13c-f646533f4ef3","year":2020},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.577277Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:582d38895060db3f7a3ef74a4cfe47d4eaea652ee64d768948738ed637b0e43e","observation_id":"905d3592-d11f-4d7f-91b3-d2f12d03cc12","resolution":{"observed_at":"2026-08-10T14:06:42.032337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.019272Z","title":"Gcs: Graph-based coordination strategy for multi-agent rein- forcement learning,","venue":null,"work_id":"23792ba7-abd6-4e23-b64d-4d6ae688c9a8","year":2022},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.579884Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:7f0765232bb624edac4b106e1b7a57b4eba517694aa8488e9afcfba3a2f663c4","observation_id":"8355cf6a-a2d4-4322-a4a3-014d3b1c6584","resolution":{"observed_at":"2026-08-10T14:06:42.022866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.009745Z","title":"Scalable multi-agent reinforcement learning through intelligent information aggregation,","venue":null,"work_id":"22ee53a3-d819-4372-912a-52d8e7b120f4","year":2023},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.582581Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:a2ee6876e368a98b9f109611d10a787c191f3fa23d6cbfd594103eaf7197055a","observation_id":"73e3ec64-8d66-41d7-880d-cb043603948a","resolution":{"observed_at":"2026-08-10T14:06:42.012941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:42.000177Z","title":"Multi-agent reinforcement learning: Independent vs. cooper- ative agents,","venue":null,"work_id":"1b81af66-81e0-4d6d-a188-85d2fc31fee8","year":1993},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.585123Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:3d6f433fb1d4fcbb4125b9a5dd1c398eab0cea1f185b0be4a89cfbd7f0010e78","observation_id":"4fd4a60a-4132-46cc-89be-d0b4a17532c7","resolution":{"observed_at":"2026-08-10T14:06:42.003298Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.990848Z","title":"I2q: A fully decentralized q-learning algorithm,","venue":null,"work_id":"8fff6225-bb10-48e9-8847-ae47b541dc2a","year":2022},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.587913Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:6df6ba77d7ca8ccfbfc20688c5a00c19a8fcbb62d40ae3bc43e655145f9bb280","observation_id":"6181af99-5c10-46ad-9bf8-000dd7647113","resolution":{"observed_at":"2026-08-10T14:06:41.994116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.982016Z","title":"Learning when to communicate at scale in multiagent cooperative and competitive tasks,","venue":null,"work_id":"69c8eb74-274f-4bf4-8bef-01c810dca2c6","year":2018},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.590469Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:e66baf04187d6fe6aac965be167bfa1bc4f9dc20ac1964bce1815e8dcbdfe19c","observation_id":"8c9e1918-6f48-429d-b061-2e7831644248","resolution":{"observed_at":"2026-08-10T14:06:41.985062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.973350Z","title":"Learning attentional communication for multi- agent cooperation,","venue":null,"work_id":"f802c4bf-07aa-4441-8117-9bed855215c9","year":2018},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.593084Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:bf593fcf95fb112c4e1b5db0fa8a85514217d7ae7bd5a7d1169ba816afba7a82","observation_id":"f60ae8c9-6936-42b0-8f14-9fca3d5f7b6c","resolution":{"observed_at":"2026-08-10T14:06:41.976440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.964299Z","title":"Tarmac: Targeted multi-agent communication,","venue":null,"work_id":"0e9591bf-77f4-4646-addb-03cb3dcbcbfc","year":2019},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.595665Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:97fbfdbfb1c8de24785db500b8469fb606aabbeb4931f4a6dd1866be6c511694","observation_id":"5e3cbe01-bc73-4945-86a3-10391d56b498","resolution":{"observed_at":"2026-08-10T14:06:41.967349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.955823Z","title":"Efficient communication in multi- agent reinforcement learning via variance based control,","venue":null,"work_id":"0a648ab5-ad1c-4887-8cef-6b9a6c7c9762","year":2019},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.598528Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:a0c43d6ff402d7b0a3fc2e058a5d664e564b98bae0181e3f843345a445a9dcf6","observation_id":"ea1eaf52-c0d5-4945-b1ac-dddf931a9685","resolution":{"observed_at":"2026-08-10T14:06:41.958857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.946935Z","title":"Who2com: Collaborative perception via learnable handshake commu- nication,","venue":null,"work_id":"eab1bde8-4efc-4670-a281-34073b67cf7e","year":2020},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.601563Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:5cbd4c65a7db3f8d56e1aecfcf956e74d8e9680892a838ec25a32179357e84a4","observation_id":"74ac02fe-5b0c-42cd-a99d-e787d823b983","resolution":{"observed_at":"2026-08-10T14:06:41.950203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.938534Z","title":"When2com: Multi-agent perception via communication graph grouping,","venue":null,"work_id":"fae591ec-84a3-49f5-acd1-b8db6220f7e7","year":2020},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.604330Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:2d234be8fa2bcd1bd48f49b24cd26d6c5cf4c7856e673c3820ae6eeb27384961","observation_id":"e1b04bc6-95c9-4433-a87c-21ac85dd740f","resolution":{"observed_at":"2026-08-10T14:06:41.941274Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.929864Z","title":"Where2comm: Communication-efficient collaborative perception via spatial confidence maps,","venue":null,"work_id":"899e737e-e8c3-4e9c-acf9-0b281b2a4a2f","year":2022},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.606936Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:fb0ee36812a89258e9669cac1e85bad3d57e28cb8f872d8f88a6c0d99af4a84c","observation_id":"060de190-cd03-48ab-8600-6e4135ed72bd","resolution":{"observed_at":"2026-08-10T14:06:41.932831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.920386Z","title":"Multi-agent incentive communication via decentralized teammate mod- eling,","venue":null,"work_id":"2cba52a9-ed62-4368-b8cb-979cc4a010e3","year":2022},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.609514Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:03c9c79561bb4e60e9e81bfd27d2b0b41e84a849b9b4bc339466f0eeb209b5ce","observation_id":"cf6d7d9b-4a56-40e5-886a-6b4e24b36ea2","resolution":{"observed_at":"2026-08-10T14:06:41.923280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.911781Z","title":"Learning efficient and robust multi-agent communication via graph information bottleneck,","venue":null,"work_id":"b4823d0b-e610-4301-8efe-c50e0a2291e0","year":2024},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.612236Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:51fd034176859426f3cfcc258e6e168e74f3d5d0f57a499a978075b60b5c58ff","observation_id":"b9bc41f0-d915-419d-9e3a-adbb33b3df91","resolution":{"observed_at":"2026-08-10T14:06:41.914700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.903481Z","title":"Expressive multi-agent communication via identity-aware learning,","venue":null,"work_id":"75aa628c-b155-46d2-87f7-a7f314cb4c02","year":2024},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.615043Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:eb8cb64f331d116280d6ec8adc720bb68ee3391f57223b616fad035cd251a80e","observation_id":"5942b017-5c76-4288-837d-0925f69e0a60","resolution":{"observed_at":"2026-08-10T14:06:41.906330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.894880Z","title":"Pmac: Personalized multi-agent communication,","venue":null,"work_id":"32178b3d-b24b-4756-9cf5-99ddb7a48cb4","year":2024},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.617747Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:7b38324e6e048e8cea9db6d82ba8d48d8078dbc3c678c47447b9ebd2f42a9d9f","observation_id":"251d6ab9-4190-48a8-9baa-011bfa881430","resolution":{"observed_at":"2026-08-10T14:06:41.897634Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.886899Z","title":"Simultaneously learning and advising in multiagent reinforcement learning,","venue":null,"work_id":"9b65ec93-ad1b-4ff8-84dd-ce0590e14436","year":2017},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.620823Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:e34865979f8363983cdf01b3ad6b24bd2275134642794e535d370131d811a469","observation_id":"0439015a-c91d-45ae-b8ec-2e2c3084eebf","resolution":{"observed_at":"2026-08-10T14:06:41.889487Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.878576Z","title":"Cautiously-optimistic knowledge sharing for cooperative multi-agent reinforcement learning,","venue":null,"work_id":"2df47a28-af92-4ac7-8d43-ded7b7504852","year":2024},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.623623Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:0dafc1fea40b3469c67c9d8cec5bebe05f240f31242e978d81cb12d0a21a3cf4","observation_id":"d6b4c6c2-5a25-471f-b97c-d06dae065291","resolution":{"observed_at":"2026-08-10T14:06:41.881682Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.869104Z","title":"Learning individually inferred commu- nication for multi-agent cooperation,","venue":null,"work_id":"c86f9c82-8787-4078-94ed-e4c170bcbc23","year":2020},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.626347Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:2a37081ec8cf82a336a336e345894aa3c4e415fd3e43a757d1dee14dcf248caf","observation_id":"8d814673-72ab-47d3-bda1-1bc5562f10b8","resolution":{"observed_at":"2026-08-10T14:06:41.872510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.859922Z","title":"Learning multi-agent communication with double attentional deep reinforcement learning,","venue":null,"work_id":"093ae827-3d4a-4d28-980f-260b9855b24e","year":2020},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.629173Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:01a188157f06028119f8c46f2d6f061d083d6f916ec52ac5fc9556f99f8f9ae9","observation_id":"e91dbe19-8aac-45b5-a05d-8f8c59af1d8b","resolution":{"observed_at":"2026-08-10T14:06:41.862985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.850451Z","title":"Value-decomposition networks for cooperative multi-agent learning based on team reward,","venue":null,"work_id":"f12255e9-d3a6-4ac7-a4d5-47ee5618680a","year":2018},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.632031Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:7d7580c6723e57913f5291c8563a05a1c9b4cf149edbfe600fd206011f64298e","observation_id":"f2ef733a-6b9a-4ee9-8ff5-872f70614435","resolution":{"observed_at":"2026-08-10T14:06:41.853587Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.841332Z","title":"Deep coordination graphs,","venue":null,"work_id":"368a28b2-2c73-4ba2-ac46-069bb12bfa82","year":2020},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.634862Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:3f5a37931273e84651ba7b03369acb9377a70b326d984d4ec4ad140a4c924155","observation_id":"6391fc64-1c56-4d08-b203-d524dc001112","resolution":{"observed_at":"2026-08-10T14:06:41.844274Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.831060Z","title":"Learning multi-agent coordination through connectivity-driven communication,","venue":null,"work_id":"a3370c69-2b73-42cf-8778-c66c0647b333","year":2023},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.637519Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:26c99514d442a983324508b2a4ff2698889f01582db2c8ee92ffefabc84b0442","observation_id":"5d9d2397-bcd6-4707-aa96-33f2dfca0024","resolution":{"observed_at":"2026-08-10T14:06:41.834387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.821276Z","title":"Settling decentralized multi-agent coordinated exploration by novelty sharing,","venue":null,"work_id":"cae88ec1-3154-449e-bfc8-a568aa8f4133","year":2024},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.640145Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:6fa770bede054029091a3c77093f0ca692c092296b8b8e8415763fb6f64518a5","observation_id":"13094969-545f-44c7-bdb0-72173ca02b9e","resolution":{"observed_at":"2026-08-10T14:06:41.824455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2011.09533","last_updated":"2020-11-18T20:29:59Z","snapshot_observed_at":"2026-08-18T16:24:34.942248Z","submitted_at":"2020-11-18T20:29:59Z","title":"Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.09533","snapshot_observed_at":"2026-08-10T14:06:41.643236Z","title":"Is independent learning all you need in the starcraft multi-agent challenge?,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.643236Z"},"links":{"cited_paper":"/paper/2011.09533","citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:695c212fa04dd42453fbf4dd00a2602b72cf7b9af3a548fe98e13e13d078e317","observation_id":"0d1d8a59-87dd-4c75-a60b-bc9de4927cef","resolution":{"observed_at":"2026-08-10T14:06:41.643236Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.811507Z","title":"V-learning–a simple, efficient, decentralized algorithm for multiagent rl,","venue":null,"work_id":"c759fb20-8a20-4bc5-88f6-75c60cd4920f","year":2022},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.646566Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:b933b646470c1dd1cb598833330ab0f4c434c5a5919e34370b63a4128304ecf1","observation_id":"34e04b78-f690-449f-b91f-8849f4e3ed04","resolution":{"observed_at":"2026-08-10T14:06:41.815053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.801810Z","title":"The complexity of markov equilibrium in stochastic games,","venue":null,"work_id":"d5a9c396-8529-4ced-9c92-803ecfd52fa0","year":2023},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.649343Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:f046ea1bfba5bde50584dcd65d42a6322acc97f10ef7831312d26d7a62113f87","observation_id":"d204b045-cbd4-4303-8f6c-6aa330384716","resolution":{"observed_at":"2026-08-10T14:06:41.805299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.792183Z","title":"Learn to follow: Decentralized lifelong multi-agent pathfinding via planning and learning,","venue":null,"work_id":"d61fdea8-f6f3-4fd9-8c96-5d0c92a1e8b9","year":2024},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.652036Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:156293409930add2c1a5ec59a66d4695f20a76c0cd8dcede534a29622dee7e5f","observation_id":"16733ee6-e0ba-42bd-810d-47614b98cb73","resolution":{"observed_at":"2026-08-10T14:06:41.795644Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.781860Z","title":"Shared experience actor- critic for multi-agent reinforcement learning,","venue":null,"work_id":"638bd13b-28e0-4911-9e47-a8c1e1a924f1","year":2020},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.654772Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:9676bffe8cfd53c75aee8a0ce324682cb4a42af1146f9906f998e03f895747a1","observation_id":"341a1803-1c60-4141-b1bc-521bcbba30bd","resolution":{"observed_at":"2026-08-10T14:06:41.785424Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.771408Z","title":"Exploration-guided reward shaping for reinforcement learning under sparse rewards,","venue":null,"work_id":"c93e5f33-dbfb-437e-81ae-e85658f041f3","year":2022},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.657441Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:91f03fe2892d2df3d494e310c8132a413b0b76a96ee52736a59f484a5996f42a","observation_id":"02c30f89-21a5-4c81-bcd2-dd112a0ae793","resolution":{"observed_at":"2026-08-10T14:06:41.774560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.760772Z","title":null,"venue":null,"work_id":"7d24c29a-1a0c-48be-b7c4-dda3f31aec5f","year":2016},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.659960Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:7865d1ad0379b73714f1f444430a955dd86e66afd9f92943ec7cf07fa1dcd548","observation_id":"4a85a0fc-44bf-492f-a13e-5896d94f5c4f","resolution":{"observed_at":"2026-08-10T14:06:41.764222Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.751010Z","title":"Universal value func- tion approximators,","venue":null,"work_id":"c09f4102-7e0a-4534-b5f4-0ed87469f668","year":2015},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.662928Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:bc6c8d5839e630d2ddd4de1768b6ff4aa92dc9026467c304b093fd2fd0f3fa56","observation_id":"f98438ea-7365-4903-ba07-1dd33446b055","resolution":{"observed_at":"2026-08-10T14:06:41.754109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.741092Z","title":"Natural actor-critic,","venue":null,"work_id":"b2efc055-1e43-4538-8c0f-9a9b64ceddbe","year":2008},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.666136Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:8bdbea8a21a5f3f40bb9d8c7bfb557dfea90d1e8172514423073cb0c0092a12d","observation_id":"6d2f3130-d65e-437b-a222-0361b0f36fc4","resolution":{"observed_at":"2026-08-10T14:06:41.743952Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T14:06:41.728873Z","title":"Continuous control with deep reinforcement learning,","venue":null,"work_id":"23423a4b-a676-4866-ba22-0d81d9ee9fbe","year":2015},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.668892Z"},"links":{"citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:aaa09def4c2c2ed48033fc56c73d2db8d1ff616f0d59cd3fe2ec1a9c43f3f5e4","observation_id":"e0d678e4-b0c5-4597-a5e5-3bd2e3bf160a","resolution":{"observed_at":"2026-08-10T14:06:41.734106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-10T14:06:41.671721Z","title":"Adam: A method for stochastic optimization,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T14:06:41.671721Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2501.15695"},"observation_digest":"sha256:5603f0b81e9bbaa9cfad165aa85486e1c9a55de38ae12cb1678cae294ec3a808","observation_id":"4458302a-e580-4a71-b452-62c72bf984bf","resolution":{"observed_at":"2026-08-10T14:06:41.671721Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.15695","last_updated":"2025-01-26T22:49:50Z","latest_version":1,"primary_category":"cs.MA","snapshot_observed_at":"2026-08-12T16:12:53.365138Z","submitted_at":"2025-01-26T22:49:50Z","title":"Contextual Knowledge Sharing in Multi-Agent Reinforcement Learning with Decentralized Communication and Coordination"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":0,"verified_fuzzy":38},"total_outbound_references":46},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 2 inbound Pith citation observations for arXiv:2501.15695."}