{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:GQMWWYQL5QYCYIGT37YDMH5PNT","short_pith_number":"pith:GQMWWYQL","schema_version":"1.0","canonical_sha256":"34196b620bec302c20d3dff0361faf6cfd8cadd8de5e8fb950ae5a87c542e203","source":{"kind":"arxiv","id":"1704.01432","version":2},"attestation_state":"computed","paper":{"title":"Probabilistic Plan Synthesis for Coupled Multi-Agent Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Alexandros Nikou, Dimos V. Dimarogonas, Jana Tumova","submitted_at":"2017-04-05T13:56:42Z","abstract_excerpt":"This paper presents a fully automated procedure for controller synthesis for multi-agent systems under the presence of uncertainties. We model the motion of each of the $N$ agents in the environment as a Markov Decision Process (MDP) and we assign to each agent one individual high-level formula given in Probabilistic Computational Tree Logic (PCTL). Each agent may need to collaborate with other agents in order to achieve a task. The collaboration is imposed by sharing actions between the agents. We aim to design local control policies such that each agent satisfies its individual PCTL formula."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1704.01432","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2017-04-05T13:56:42Z","cross_cats_sorted":[],"title_canon_sha256":"03e50d41795e9b9f7f8c9fb178bd5bdc4cd883de6968f9fb7228858b4c1b4b78","abstract_canon_sha256":"2e0fd8111c003118a3b74991bb0ad185be5b9e9ebc643807921f81867386460c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:44:56.998823Z","signature_b64":"STsdtHDTHIXABCtWPb5P2J3Lmhwtw6Y2oM5SMfqLrk4NmL2YVKdUklT9LUNAXbhZHl7VKMBnZloW/t2PfuevAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"34196b620bec302c20d3dff0361faf6cfd8cadd8de5e8fb950ae5a87c542e203","last_reissued_at":"2026-05-18T00:44:56.998194Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:44:56.998194Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Probabilistic Plan Synthesis for Coupled Multi-Agent Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Alexandros Nikou, Dimos V. Dimarogonas, Jana Tumova","submitted_at":"2017-04-05T13:56:42Z","abstract_excerpt":"This paper presents a fully automated procedure for controller synthesis for multi-agent systems under the presence of uncertainties. We model the motion of each of the $N$ agents in the environment as a Markov Decision Process (MDP) and we assign to each agent one individual high-level formula given in Probabilistic Computational Tree Logic (PCTL). Each agent may need to collaborate with other agents in order to achieve a task. The collaboration is imposed by sharing actions between the agents. We aim to design local control policies such that each agent satisfies its individual PCTL formula."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.01432","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1704.01432","created_at":"2026-05-18T00:44:56.998294+00:00"},{"alias_kind":"arxiv_version","alias_value":"1704.01432v2","created_at":"2026-05-18T00:44:56.998294+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.01432","created_at":"2026-05-18T00:44:56.998294+00:00"},{"alias_kind":"pith_short_12","alias_value":"GQMWWYQL5QYC","created_at":"2026-05-18T12:31:18.294218+00:00"},{"alias_kind":"pith_short_16","alias_value":"GQMWWYQL5QYCYIGT","created_at":"2026-05-18T12:31:18.294218+00:00"},{"alias_kind":"pith_short_8","alias_value":"GQMWWYQL","created_at":"2026-05-18T12:31:18.294218+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/GQMWWYQL5QYCYIGT37YDMH5PNT","json":"https://pith.science/pith/GQMWWYQL5QYCYIGT37YDMH5PNT.json","graph_json":"https://pith.science/api/pith-number/GQMWWYQL5QYCYIGT37YDMH5PNT/graph.json","events_json":"https://pith.science/api/pith-number/GQMWWYQL5QYCYIGT37YDMH5PNT/events.json","paper":"https://pith.science/paper/GQMWWYQL"},"agent_actions":{"view_html":"https://pith.science/pith/GQMWWYQL5QYCYIGT37YDMH5PNT","download_json":"https://pith.science/pith/GQMWWYQL5QYCYIGT37YDMH5PNT.json","view_paper":"https://pith.science/paper/GQMWWYQL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1704.01432&json=true","fetch_graph":"https://pith.science/api/pith-number/GQMWWYQL5QYCYIGT37YDMH5PNT/graph.json","fetch_events":"https://pith.science/api/pith-number/GQMWWYQL5QYCYIGT37YDMH5PNT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GQMWWYQL5QYCYIGT37YDMH5PNT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GQMWWYQL5QYCYIGT37YDMH5PNT/action/storage_attestation","attest_author":"https://pith.science/pith/GQMWWYQL5QYCYIGT37YDMH5PNT/action/author_attestation","sign_citation":"https://pith.science/pith/GQMWWYQL5QYCYIGT37YDMH5PNT/action/citation_signature","submit_replication":"https://pith.science/pith/GQMWWYQL5QYCYIGT37YDMH5PNT/action/replication_record"}},"created_at":"2026-05-18T00:44:56.998294+00:00","updated_at":"2026-05-18T00:44:56.998294+00:00"}