{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:ORB2PHK623BESQY5U4IL6G7QWE","short_pith_number":"pith:ORB2PHK6","canonical_record":{"source":{"id":"1911.10868","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-25T12:34:26Z","cross_cats_sorted":["cs.AI","cs.CV","cs.RO","stat.ML"],"title_canon_sha256":"314b80f5e9206023415875b6dfc29dd8e57a5e7b3f2ef4e9a4c08459109dfc41","abstract_canon_sha256":"d7118a08fb9c8c1d0e647402102c1b84cb1cb52eb5e51c46b344fe3bfa1cf7b7"},"schema_version":"1.0"},"canonical_sha256":"7443a79d5ed6c249431da710bf1bf0b122ad454f6a3a37512f6ad45f1699a851","source":{"kind":"arxiv","id":"1911.10868","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.10868","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"arxiv_version","alias_value":"1911.10868v2","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.10868","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"pith_short_12","alias_value":"ORB2PHK623BE","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"pith_short_16","alias_value":"ORB2PHK623BESQY5","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"pith_short_8","alias_value":"ORB2PHK6","created_at":"2026-07-05T00:48:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:ORB2PHK623BESQY5U4IL6G7QWE","target":"record","payload":{"canonical_record":{"source":{"id":"1911.10868","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-25T12:34:26Z","cross_cats_sorted":["cs.AI","cs.CV","cs.RO","stat.ML"],"title_canon_sha256":"314b80f5e9206023415875b6dfc29dd8e57a5e7b3f2ef4e9a4c08459109dfc41","abstract_canon_sha256":"d7118a08fb9c8c1d0e647402102c1b84cb1cb52eb5e51c46b344fe3bfa1cf7b7"},"schema_version":"1.0"},"canonical_sha256":"7443a79d5ed6c249431da710bf1bf0b122ad454f6a3a37512f6ad45f1699a851","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:48:00.964382Z","signature_b64":"VjROEm8jewnYBD7oXQv6bN7o0rN76PRa803Z3PJkGyc+nm5a3gNxVtYhIZav6EUFYFO/Klu1AyMWG9WZoCK6BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7443a79d5ed6c249431da710bf1bf0b122ad454f6a3a37512f6ad45f1699a851","last_reissued_at":"2026-07-05T00:48:00.963980Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:48:00.963980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1911.10868","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:48:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UI1zeQFsLeSoNB65byXEEyGj/rhjbeXzm0H/+1KOpXD/t+cXPfGv7DYiikxyXhmdUmUbv7wxgvijhKd3Ot4lBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T20:52:48.032324Z"},"content_sha256":"2c0402c6db9d8bd0b9c2c5789b76568a04fd0cf16c7733fd5ff3085616f3794d","schema_version":"1.0","event_id":"sha256:2c0402c6db9d8bd0b9c2c5789b76568a04fd0cf16c7733fd5ff3085616f3794d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:ORB2PHK623BESQY5U4IL6G7QWE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.RO","stat.ML"],"primary_cat":"cs.LG","authors_text":"Emilie Wirbel, Fabien Moutarde, Marin Toromanoff","submitted_at":"2019-11-25T12:34:26Z","abstract_excerpt":"Reinforcement Learning (RL) aims at learning an optimal behavior policy from its own experiments and not rule-based control methods. However, there is no RL algorithm yet capable of handling a task as difficult as urban driving. We present a novel technique, coined implicit affordances, to effectively leverage RL for urban driving thus including lane keeping, pedestrians and vehicles avoidance, and traffic light detection. To our knowledge we are the first to present a successful RL agent handling such a complex task especially regarding the traffic light detection. Furthermore, we have demons"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.10868","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1911.10868/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:48:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Jqs5++3QzhM9qtWri82LvO6sJ9v5t3f6grPmmCMvXPLnz/BAGaHu6fOZNc6gWjDSyUWXWf2y7IvKpClO/W9iAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T20:52:48.032709Z"},"content_sha256":"f835e76593024a614d51e84f023ac34225bbda221e2ad83c10febddff29b4708","schema_version":"1.0","event_id":"sha256:f835e76593024a614d51e84f023ac34225bbda221e2ad83c10febddff29b4708"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ORB2PHK623BESQY5U4IL6G7QWE/bundle.json","state_url":"https://pith.science/pith/ORB2PHK623BESQY5U4IL6G7QWE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ORB2PHK623BESQY5U4IL6G7QWE/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T20:52:48Z","links":{"resolver":"https://pith.science/pith/ORB2PHK623BESQY5U4IL6G7QWE","bundle":"https://pith.science/pith/ORB2PHK623BESQY5U4IL6G7QWE/bundle.json","state":"https://pith.science/pith/ORB2PHK623BESQY5U4IL6G7QWE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ORB2PHK623BESQY5U4IL6G7QWE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ORB2PHK623BESQY5U4IL6G7QWE","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":"d7118a08fb9c8c1d0e647402102c1b84cb1cb52eb5e51c46b344fe3bfa1cf7b7","cross_cats_sorted":["cs.AI","cs.CV","cs.RO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-25T12:34:26Z","title_canon_sha256":"314b80f5e9206023415875b6dfc29dd8e57a5e7b3f2ef4e9a4c08459109dfc41"},"schema_version":"1.0","source":{"id":"1911.10868","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.10868","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"arxiv_version","alias_value":"1911.10868v2","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.10868","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"pith_short_12","alias_value":"ORB2PHK623BE","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"pith_short_16","alias_value":"ORB2PHK623BESQY5","created_at":"2026-07-05T00:48:00Z"},{"alias_kind":"pith_short_8","alias_value":"ORB2PHK6","created_at":"2026-07-05T00:48:00Z"}],"graph_snapshots":[{"event_id":"sha256:f835e76593024a614d51e84f023ac34225bbda221e2ad83c10febddff29b4708","target":"graph","created_at":"2026-07-05T00:48:00Z","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/1911.10868/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reinforcement Learning (RL) aims at learning an optimal behavior policy from its own experiments and not rule-based control methods. However, there is no RL algorithm yet capable of handling a task as difficult as urban driving. We present a novel technique, coined implicit affordances, to effectively leverage RL for urban driving thus including lane keeping, pedestrians and vehicles avoidance, and traffic light detection. To our knowledge we are the first to present a successful RL agent handling such a complex task especially regarding the traffic light detection. Furthermore, we have demons","authors_text":"Emilie Wirbel, Fabien Moutarde, Marin Toromanoff","cross_cats":["cs.AI","cs.CV","cs.RO","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-25T12:34:26Z","title":"End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.10868","kind":"arxiv","version":2},"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":"sha256:2c0402c6db9d8bd0b9c2c5789b76568a04fd0cf16c7733fd5ff3085616f3794d","target":"record","created_at":"2026-07-05T00:48:00Z","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":"d7118a08fb9c8c1d0e647402102c1b84cb1cb52eb5e51c46b344fe3bfa1cf7b7","cross_cats_sorted":["cs.AI","cs.CV","cs.RO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-25T12:34:26Z","title_canon_sha256":"314b80f5e9206023415875b6dfc29dd8e57a5e7b3f2ef4e9a4c08459109dfc41"},"schema_version":"1.0","source":{"id":"1911.10868","kind":"arxiv","version":2}},"canonical_sha256":"7443a79d5ed6c249431da710bf1bf0b122ad454f6a3a37512f6ad45f1699a851","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7443a79d5ed6c249431da710bf1bf0b122ad454f6a3a37512f6ad45f1699a851","first_computed_at":"2026-07-05T00:48:00.963980Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:48:00.963980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VjROEm8jewnYBD7oXQv6bN7o0rN76PRa803Z3PJkGyc+nm5a3gNxVtYhIZav6EUFYFO/Klu1AyMWG9WZoCK6BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:48:00.964382Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.10868","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c0402c6db9d8bd0b9c2c5789b76568a04fd0cf16c7733fd5ff3085616f3794d","sha256:f835e76593024a614d51e84f023ac34225bbda221e2ad83c10febddff29b4708"],"state_sha256":"ced68349445ee0e7d411a8e6025294f377363ff86762a98f05705d1b0fae835c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LYt9bzGS89RotZ4MwSKShjhEXj2C12ARXvbfctGkeKzU0ni4KYfGSess7u4W4oVZe5al/X5d/g07ITWlq4ZkBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T20:52:48.035188Z","bundle_sha256":"f44221a8ee5c923e7b73324d24f45a6edfde69086de914ff9ab2e033dd7ab7bc"}}