{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:O7AQ74GTY52BO3MGMPHBTE222X","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"0b03e66743b485019666802a0e8ccaa8399b058f43ae60a9af4a2f89d851ba86","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T00:00:11Z","title_canon_sha256":"c2a411facfc0c288972ec78c1a123cd6dcfeb057c1a80669013d03b51fe85c7c"},"schema_version":"1.0","source":{"id":"2501.14992","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.14992","created_at":"2026-07-05T10:05:21Z"},{"alias_kind":"arxiv_version","alias_value":"2501.14992v1","created_at":"2026-07-05T10:05:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.14992","created_at":"2026-07-05T10:05:21Z"},{"alias_kind":"pith_short_12","alias_value":"O7AQ74GTY52B","created_at":"2026-07-05T10:05:21Z"},{"alias_kind":"pith_short_16","alias_value":"O7AQ74GTY52BO3MG","created_at":"2026-07-05T10:05:21Z"},{"alias_kind":"pith_short_8","alias_value":"O7AQ74GT","created_at":"2026-07-05T10:05:21Z"}],"graph_snapshots":[{"event_id":"sha256:298398f5b6af02d07249468bbc5e0468116148e634f1f265551b552c8d0e650e","target":"graph","created_at":"2026-07-05T10:05:21Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2501.14992/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Developing an automated driving system capable of navigating complex traffic environments remains a formidable challenge. Unlike rule-based or supervised learning-based methods, Deep Reinforcement Learning (DRL) based controllers eliminate the need for domain-specific knowledge and datasets, thus providing adaptability to various scenarios. Nonetheless, a common limitation of existing studies on DRL-based controllers is their focus on driving scenarios with simple traffic patterns, which hinders their capability to effectively handle complex driving environments with delayed, long-term rewards","authors_text":"Ekim Yurtsever, Keith A. Redmill, Zhihao Zhang","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T00:00:11Z","title":"Extensive Exploration in Complex Traffic Scenarios using Hierarchical Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.14992","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:83ea29ff9b3d5abed20c9adbf4f949585f688821765345c40ec6da98f635b41c","target":"record","created_at":"2026-07-05T10:05:21Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"0b03e66743b485019666802a0e8ccaa8399b058f43ae60a9af4a2f89d851ba86","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T00:00:11Z","title_canon_sha256":"c2a411facfc0c288972ec78c1a123cd6dcfeb057c1a80669013d03b51fe85c7c"},"schema_version":"1.0","source":{"id":"2501.14992","kind":"arxiv","version":1}},"canonical_sha256":"77c10ff0d3c774176d8663ce19935ad5d1094a823077c7df1f120b0dee865f9e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"77c10ff0d3c774176d8663ce19935ad5d1094a823077c7df1f120b0dee865f9e","first_computed_at":"2026-07-05T10:05:21.787740Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:05:21.787740Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1n0raKNWD0ZYehTU48zYkH6vOx+A5lZfzwyULFWeoZW+PuUwscWDcL7EXVYk/sUxz5boGucI1tsldvZHnkBKAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:05:21.788230Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.14992","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:83ea29ff9b3d5abed20c9adbf4f949585f688821765345c40ec6da98f635b41c","sha256:298398f5b6af02d07249468bbc5e0468116148e634f1f265551b552c8d0e650e"],"state_sha256":"cd30cbaa17bfd955e8acd302c643478aded4dab7557ffa9a6f301c61e74f65f5"}