{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:HWHCH2JZZKQBO4ZZ2VI53YOLFV","short_pith_number":"pith:HWHCH2JZ","schema_version":"1.0","canonical_sha256":"3d8e23e939caa0177339d551dde1cb2d4b56b9877c8d890219fee9492795e2fa","source":{"kind":"arxiv","id":"1905.05637","version":1},"attestation_state":"computed","paper":{"title":"Randomized Adversarial Imitation Learning for Autonomous Driving","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Joongheon Kim, MyungJae Shin","submitted_at":"2019-05-13T14:27:00Z","abstract_excerpt":"With the evolution of various advanced driver assistance system (ADAS) platforms, the design of autonomous driving system is becoming more complex and safety-critical. The autonomous driving system simultaneously activates multiple ADAS functions; and thus it is essential to coordinate various ADAS functions. This paper proposes a randomized adversarial imitation learning (RAIL) method that imitates the coordination of autonomous vehicle equipped with advanced sensors. The RAIL policies are trained through derivative-free optimization for the decision maker that coordinates the proper ADAS fun"},"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":"1905.05637","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-05-13T14:27:00Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"dc678814c411e062a18f5afa0b7f68292e1139ea95d6708c0f270c0ac53d14bc","abstract_canon_sha256":"49e718bc14f8a774a12a4159e2c1b3d64fb46f94295d3e8e7c21d8c996f96c2d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:46:13.989446Z","signature_b64":"c9yR01+88WhRnKU2l5seBbAlKAUnESyILxIsoABLVRdoAnXM+Q49oe1CC+UqMwLUp9sU3LxODzo4zw2VhcvQBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3d8e23e939caa0177339d551dde1cb2d4b56b9877c8d890219fee9492795e2fa","last_reissued_at":"2026-05-17T23:46:13.988861Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:46:13.988861Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Randomized Adversarial Imitation Learning for Autonomous Driving","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Joongheon Kim, MyungJae Shin","submitted_at":"2019-05-13T14:27:00Z","abstract_excerpt":"With the evolution of various advanced driver assistance system (ADAS) platforms, the design of autonomous driving system is becoming more complex and safety-critical. The autonomous driving system simultaneously activates multiple ADAS functions; and thus it is essential to coordinate various ADAS functions. This paper proposes a randomized adversarial imitation learning (RAIL) method that imitates the coordination of autonomous vehicle equipped with advanced sensors. The RAIL policies are trained through derivative-free optimization for the decision maker that coordinates the proper ADAS fun"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.05637","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":""},"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":"1905.05637","created_at":"2026-05-17T23:46:13.988973+00:00"},{"alias_kind":"arxiv_version","alias_value":"1905.05637v1","created_at":"2026-05-17T23:46:13.988973+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.05637","created_at":"2026-05-17T23:46:13.988973+00:00"},{"alias_kind":"pith_short_12","alias_value":"HWHCH2JZZKQB","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_16","alias_value":"HWHCH2JZZKQBO4ZZ","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_8","alias_value":"HWHCH2JZ","created_at":"2026-05-18T12:33:18.533446+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/HWHCH2JZZKQBO4ZZ2VI53YOLFV","json":"https://pith.science/pith/HWHCH2JZZKQBO4ZZ2VI53YOLFV.json","graph_json":"https://pith.science/api/pith-number/HWHCH2JZZKQBO4ZZ2VI53YOLFV/graph.json","events_json":"https://pith.science/api/pith-number/HWHCH2JZZKQBO4ZZ2VI53YOLFV/events.json","paper":"https://pith.science/paper/HWHCH2JZ"},"agent_actions":{"view_html":"https://pith.science/pith/HWHCH2JZZKQBO4ZZ2VI53YOLFV","download_json":"https://pith.science/pith/HWHCH2JZZKQBO4ZZ2VI53YOLFV.json","view_paper":"https://pith.science/paper/HWHCH2JZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1905.05637&json=true","fetch_graph":"https://pith.science/api/pith-number/HWHCH2JZZKQBO4ZZ2VI53YOLFV/graph.json","fetch_events":"https://pith.science/api/pith-number/HWHCH2JZZKQBO4ZZ2VI53YOLFV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HWHCH2JZZKQBO4ZZ2VI53YOLFV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HWHCH2JZZKQBO4ZZ2VI53YOLFV/action/storage_attestation","attest_author":"https://pith.science/pith/HWHCH2JZZKQBO4ZZ2VI53YOLFV/action/author_attestation","sign_citation":"https://pith.science/pith/HWHCH2JZZKQBO4ZZ2VI53YOLFV/action/citation_signature","submit_replication":"https://pith.science/pith/HWHCH2JZZKQBO4ZZ2VI53YOLFV/action/replication_record"}},"created_at":"2026-05-17T23:46:13.988973+00:00","updated_at":"2026-05-17T23:46:13.988973+00:00"}