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Paper Citation Record · LEDGER

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents

As of 11 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2508.14131.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.14131 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:01:25.746947Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

  • verified exact2
  • verified fuzzy9
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 043a0121-623d-405a-8acf-2b0998f467ef · outbound

This paper cites cooperative agents.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents cooperative agents

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:01:43.446859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:24.560268Z digest=sha256:d25ed9fd7d15b049b22fb492a1e968dffe877ccd84d07ff1d991308cf8ad0dd1

Observation 151293dc-5cc2-41aa-8eea-fa547cec58d6 · outbound

This paper cites an unresolved cited work.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-05T19:01:43.294825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:24.613730Z digest=sha256:818110dabd04f2e971658b2834726705800fa8a4ec71be7a70595b165a8b5d44

Observation 5dac44fd-5103-4128-96ab-8a5ba1832ab6 · outbound

This paper cites Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T19:01:24.672474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:01:24.672474Z digest=sha256:459c32ae12efda5fda7410bafed0b3a70aa90f25931a995665088513289deaff

Observation 1bdc3a36-f70a-4835-85d5-defe95fe985a · outbound

This paper cites an unresolved cited work.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-05T19:01:43.110159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:24.759562Z digest=sha256:cb095b7ce5a9d302d6f7c3999cb15e22600d52e02800468d82f933cd7aaad603

Observation 500dac7a-57af-4f21-86dc-4fdc9dc403c7 · outbound

This paper cites an unresolved cited work.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Unresolved cited work

Reference 5

Resolution
metadata mismatch
raw_fallback, observed 2026-08-05T19:01:41.504040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:24.856241Z digest=sha256:9e147b365876a5f3c8ccdfe9d25f1cf1c86454b91c86f2bd3d3bc704c5e54105

Observation 6c184e88-e48a-44a4-b52b-559d6407adef · outbound

This paper cites Proximal Policy Optimization Algorithms.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Proximal Policy Optimization Algorithms

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T19:01:24.930659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:01:24.930659Z digest=sha256:af0cde3bc73d523efb963485a23a23b76373a35443beb8aab0e44fe6b66a5017

Observation 8e0e80c6-e0fa-4a7b-a2a5-d50c512acbb0 · outbound

This paper cites Multi-agent actor-critic for mixed cooperative- competitive environments[J].

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Multi-agent actor-critic for mixed cooperative- competitive environments[J]

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:01:42.947513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.023437Z digest=sha256:440bdd3b12f78fad3d528d9daced253ba88858cb8b173d82e751aa77850bbe5f

Observation 92094604-43a0-4534-8d2f-3fa40d98677a · outbound

This paper cites A Concise Introduction to Decentralized POMDPs[M].

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents A Concise Introduction to Decentralized POMDPs[M]

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:01:42.806490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.110955Z digest=sha256:ed63ce0624d9cb14318ec4f929d0109899f8c63cc726d5ee2ca98b41e6eb4505

Observation 7e269cbe-8c9b-43b4-9f90-2d251ed12abe · outbound

This paper cites Cooperative multi-agent control using deep reinforcement learning[C]//International Conference on Autonomous Agents and Multiagent Systems.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Cooperative multi-agent control using deep reinforcement learning[C]//International Conference on Autonomous Agents and Multiagent Systems

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:01:42.623696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.176381Z digest=sha256:4786ff805a801407dad4365ed601841b01d2447c5116f52ae71a3694f37fe470

Observation fef48fc7-88c1-471a-9e50-d0874e5a0944 · outbound

This paper cites Learning to communicate with deep multi -agent reinforcement learning[C]//Advances in Neural Information Processing Systems.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Learning to communicate with deep multi -agent reinforcement learning[C]//Advances in Neural Information Processing Systems

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:01:42.457021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.239899Z digest=sha256:17d2c5f629a5296bd028a371c12532e7861e698fe51c0d50d8248d2081a58fcc

Observation 70b407a2-6915-4a11-9762-2beae3f77480 · outbound

This paper cites Partially Observable Mean Field Multi-Agent Reinforcement Learning Based on Graph-Attention.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Partially Observable Mean Field Multi-Agent Reinforcement Learning Based on Graph-Attention

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-05T19:01:26.289546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.332725Z digest=sha256:ba403e2e288024e5cfebc22b85411f082eb36e29024ebb88b245e830ab410617

Observation 694cd9b3-7bf5-4c13-b009-33238870db10 · outbound

This paper cites Multi-agent reinforcement learning: A review of challenges and applications[J].

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Multi-agent reinforcement learning: A review of challenges and applications[J]

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:01:42.275661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.404041Z digest=sha256:21faacf724f50c171b19793546c917d014e3b682127db7e5d3163aecc3defdd9

Observation 8559e8bf-c634-469e-b016-654a1abc7ca7 · outbound

This paper cites Coordinating multi-agent reinforcement learning with limited communication[C]//Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Coordinating multi-agent reinforcement learning with limited communication[C]//Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:01:42.057441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.418088Z digest=sha256:18bb64437734037f49d1b417f0bd80a5312f2018371c8b0e1f2d394cadd0394c

Observation 5fe9f3c6-d817-4f65-96d3-2350215d50b4 · outbound

This paper cites QMIX: Monotonic value function factorisation for deep multi-agent reinforcement learning[C]//International Conference on Machine Learning.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents QMIX: Monotonic value function factorisation for deep multi-agent reinforcement learning[C]//International Conference on Machine Learning

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:01:41.909163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.496675Z digest=sha256:bab7e5229c22cbcf0d6f6514f99497afb8ece401319b26baaf0c346226b50577

Observation 8415b5bd-6871-40c2-880d-c52f651dc095 · outbound

This paper cites Tesseract: Tensorised Actors for Multi- Agent Reinforcement Learning[C]//International Conference on Machine Learning.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Tesseract: Tensorised Actors for Multi- Agent Reinforcement Learning[C]//International Conference on Machine Learning

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T19:01:41.691669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.568589Z digest=sha256:937e4f109c2c0d7bb629c1a35c7482111ac7dbc469019128384e76dd46bcee4d

Observation 2abce512-9734-46a9-acc7-af9c0fe8f909 · outbound

This paper cites Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative Exploration.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative Exploration

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T19:01:25.675241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:01:25.675241Z digest=sha256:34ed6ce0efc10ca653f1b77ff68a32b193e913f59851c360721d4aa53085a5e7

Observation dda40da9-881a-4b8d-9e3d-6b7ccd9a7433 · outbound

This paper cites Imitation Learning with Concurrent Actions in 3D Games.

An Improved Multi-Agent Algorithm for Cooperative and Competitive Environments by Identifying and Encouraging Cooperation among Agents Imitation Learning with Concurrent Actions in 3D Games

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-05T19:01:26.080383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T19:01:25.746947Z digest=sha256:1ed9bd82e9415ac54088df9c9aedfd6d66051b97ce96b9caa872df2be8cf4205

Pith citing papers

No inbound Pith citation observations are available.