{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:6T72XSN2ZUPLL2QNIWL5P65Q56","short_pith_number":"pith:6T72XSN2","schema_version":"1.0","canonical_sha256":"f4ffabc9bacd1eb5ea0d4597d7fbb0ef8ba7f5aaafafd46742ec022d5481a4bc","source":{"kind":"arxiv","id":"2505.23846","version":1},"attestation_state":"computed","paper":{"title":"Scalable, Symbiotic, AI and Non-AI Agent Based Parallel Discrete Event Simulations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"cs.CL","authors_text":"Atanu Barai, Nandakishore Santhi, Stephan Eidenbenz","submitted_at":"2025-05-28T17:50:01Z","abstract_excerpt":"To fully leverage the potential of artificial intelligence (AI) systems in a trustworthy manner, it is desirable to couple multiple AI and non-AI systems together seamlessly for constraining and ensuring correctness of the output. This paper introduces a novel parallel discrete event simulation (PDES) based methodology to combine multiple AI and non-AI agents in a causal, rule-based way. Our approach tightly integrates the concept of passage of time, with each agent considered as an entity in the PDES framework and responding to prior requests from other agents. Such coupling mechanism enables"},"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":"2505.23846","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-28T17:50:01Z","cross_cats_sorted":["cs.MA"],"title_canon_sha256":"1ac7b4a7be5bee4565fc649629d3f119ff25077794e11b09c2c32e8cae6bf015","abstract_canon_sha256":"1197512af1365852f52e073fb9cd2f060fe721f8c5c667d6a314270deb7f8f94"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:12:36.630784Z","signature_b64":"7UlWw/6orXpiFqqJlMRneSqMsnhtS/UBQLsnW7Jg+XF5bVk4sdUcQ8+E3XhUNEiK7zDSD9Jax7H0bcaL4aHHAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f4ffabc9bacd1eb5ea0d4597d7fbb0ef8ba7f5aaafafd46742ec022d5481a4bc","last_reissued_at":"2026-07-05T11:12:36.630289Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:12:36.630289Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Scalable, Symbiotic, AI and Non-AI Agent Based Parallel Discrete Event Simulations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"cs.CL","authors_text":"Atanu Barai, Nandakishore Santhi, Stephan Eidenbenz","submitted_at":"2025-05-28T17:50:01Z","abstract_excerpt":"To fully leverage the potential of artificial intelligence (AI) systems in a trustworthy manner, it is desirable to couple multiple AI and non-AI systems together seamlessly for constraining and ensuring correctness of the output. This paper introduces a novel parallel discrete event simulation (PDES) based methodology to combine multiple AI and non-AI agents in a causal, rule-based way. Our approach tightly integrates the concept of passage of time, with each agent considered as an entity in the PDES framework and responding to prior requests from other agents. Such coupling mechanism enables"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.23846","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2505.23846/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2505.23846","created_at":"2026-07-05T11:12:36.630356+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.23846v1","created_at":"2026-07-05T11:12:36.630356+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.23846","created_at":"2026-07-05T11:12:36.630356+00:00"},{"alias_kind":"pith_short_12","alias_value":"6T72XSN2ZUPL","created_at":"2026-07-05T11:12:36.630356+00:00"},{"alias_kind":"pith_short_16","alias_value":"6T72XSN2ZUPLL2QN","created_at":"2026-07-05T11:12:36.630356+00:00"},{"alias_kind":"pith_short_8","alias_value":"6T72XSN2","created_at":"2026-07-05T11:12:36.630356+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2603.03784","citing_title":"Specification-Driven Generation and Evaluation of Discrete-Event World Models via the DEVS Formalism","ref_index":10,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6T72XSN2ZUPLL2QNIWL5P65Q56","json":"https://pith.science/pith/6T72XSN2ZUPLL2QNIWL5P65Q56.json","graph_json":"https://pith.science/api/pith-number/6T72XSN2ZUPLL2QNIWL5P65Q56/graph.json","events_json":"https://pith.science/api/pith-number/6T72XSN2ZUPLL2QNIWL5P65Q56/events.json","paper":"https://pith.science/paper/6T72XSN2"},"agent_actions":{"view_html":"https://pith.science/pith/6T72XSN2ZUPLL2QNIWL5P65Q56","download_json":"https://pith.science/pith/6T72XSN2ZUPLL2QNIWL5P65Q56.json","view_paper":"https://pith.science/paper/6T72XSN2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.23846&json=true","fetch_graph":"https://pith.science/api/pith-number/6T72XSN2ZUPLL2QNIWL5P65Q56/graph.json","fetch_events":"https://pith.science/api/pith-number/6T72XSN2ZUPLL2QNIWL5P65Q56/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6T72XSN2ZUPLL2QNIWL5P65Q56/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6T72XSN2ZUPLL2QNIWL5P65Q56/action/storage_attestation","attest_author":"https://pith.science/pith/6T72XSN2ZUPLL2QNIWL5P65Q56/action/author_attestation","sign_citation":"https://pith.science/pith/6T72XSN2ZUPLL2QNIWL5P65Q56/action/citation_signature","submit_replication":"https://pith.science/pith/6T72XSN2ZUPLL2QNIWL5P65Q56/action/replication_record"}},"created_at":"2026-07-05T11:12:36.630356+00:00","updated_at":"2026-07-05T11:12:36.630356+00:00"}