{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:IGHV2IPITLBXYTVRLUCP6GDXJ5","short_pith_number":"pith:IGHV2IPI","schema_version":"1.0","canonical_sha256":"418f5d21e89ac37c4eb15d04ff18774f5baa80698d05ef07b2aaf7e13d498190","source":{"kind":"arxiv","id":"2109.13036","version":1},"attestation_state":"computed","paper":{"title":"Learning Attacker's Bounded Rationality Model in Security Games","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.GT","authors_text":"Adam \\.Zychowski, Jacek Ma\\'ndziuk","submitted_at":"2021-09-27T13:22:30Z","abstract_excerpt":"The paper proposes a novel neuroevolutionary method (NESG) for calculating leader's payoff in Stackelberg Security Games. The heart of NESG is strategy evaluation neural network (SENN). SENN is able to effectively evaluate leader's strategies against an opponent who may potentially not behave in a perfectly rational way due to certain cognitive biases or limitations. SENN is trained on historical data and does not require any direct prior knowledge regarding the follower's target preferences, payoff distribution or bounded rationality model. NESG was tested on a set of 90 benchmark games inspi"},"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":"2109.13036","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GT","submitted_at":"2021-09-27T13:22:30Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"a3de455be69f8e98bbbc0f49d0eb06fe48a11543e72fd3b01196fa97aba7f874","abstract_canon_sha256":"543abe84754ba4b45432313416b1a8f78ab259fe9e2a1b5cfebcd300928d9828"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:48:08.177522Z","signature_b64":"INXDGnxZDCM3KeolnEEh1loydk7aLpxLck1GEnczqKfnNhLFoaAWBTug0Fbh/ux9AaDFHIOHbN0ql9vfoGJmAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"418f5d21e89ac37c4eb15d04ff18774f5baa80698d05ef07b2aaf7e13d498190","last_reissued_at":"2026-07-05T04:48:08.177172Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:48:08.177172Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning Attacker's Bounded Rationality Model in Security Games","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.GT","authors_text":"Adam \\.Zychowski, Jacek Ma\\'ndziuk","submitted_at":"2021-09-27T13:22:30Z","abstract_excerpt":"The paper proposes a novel neuroevolutionary method (NESG) for calculating leader's payoff in Stackelberg Security Games. The heart of NESG is strategy evaluation neural network (SENN). SENN is able to effectively evaluate leader's strategies against an opponent who may potentially not behave in a perfectly rational way due to certain cognitive biases or limitations. SENN is trained on historical data and does not require any direct prior knowledge regarding the follower's target preferences, payoff distribution or bounded rationality model. NESG was tested on a set of 90 benchmark games inspi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.13036","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/2109.13036/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":"2109.13036","created_at":"2026-07-05T04:48:08.177226+00:00"},{"alias_kind":"arxiv_version","alias_value":"2109.13036v1","created_at":"2026-07-05T04:48:08.177226+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.13036","created_at":"2026-07-05T04:48:08.177226+00:00"},{"alias_kind":"pith_short_12","alias_value":"IGHV2IPITLBX","created_at":"2026-07-05T04:48:08.177226+00:00"},{"alias_kind":"pith_short_16","alias_value":"IGHV2IPITLBXYTVR","created_at":"2026-07-05T04:48:08.177226+00:00"},{"alias_kind":"pith_short_8","alias_value":"IGHV2IPI","created_at":"2026-07-05T04:48:08.177226+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/IGHV2IPITLBXYTVRLUCP6GDXJ5","json":"https://pith.science/pith/IGHV2IPITLBXYTVRLUCP6GDXJ5.json","graph_json":"https://pith.science/api/pith-number/IGHV2IPITLBXYTVRLUCP6GDXJ5/graph.json","events_json":"https://pith.science/api/pith-number/IGHV2IPITLBXYTVRLUCP6GDXJ5/events.json","paper":"https://pith.science/paper/IGHV2IPI"},"agent_actions":{"view_html":"https://pith.science/pith/IGHV2IPITLBXYTVRLUCP6GDXJ5","download_json":"https://pith.science/pith/IGHV2IPITLBXYTVRLUCP6GDXJ5.json","view_paper":"https://pith.science/paper/IGHV2IPI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2109.13036&json=true","fetch_graph":"https://pith.science/api/pith-number/IGHV2IPITLBXYTVRLUCP6GDXJ5/graph.json","fetch_events":"https://pith.science/api/pith-number/IGHV2IPITLBXYTVRLUCP6GDXJ5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IGHV2IPITLBXYTVRLUCP6GDXJ5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IGHV2IPITLBXYTVRLUCP6GDXJ5/action/storage_attestation","attest_author":"https://pith.science/pith/IGHV2IPITLBXYTVRLUCP6GDXJ5/action/author_attestation","sign_citation":"https://pith.science/pith/IGHV2IPITLBXYTVRLUCP6GDXJ5/action/citation_signature","submit_replication":"https://pith.science/pith/IGHV2IPITLBXYTVRLUCP6GDXJ5/action/replication_record"}},"created_at":"2026-07-05T04:48:08.177226+00:00","updated_at":"2026-07-05T04:48:08.177226+00:00"}