{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:5ORD5BKPMRH2UDKK7X7VVCLBFO","short_pith_number":"pith:5ORD5BKP","canonical_record":{"source":{"id":"2010.08819","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-17T16:20:33Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"81e1c0d1e45159f6509b2d794640941c62789f18634040f018e2f2025888d8f5","abstract_canon_sha256":"7de556b84d776fa9db3984fb07baf48b58ae5023287a70a2c7baad242fda17ca"},"schema_version":"1.0"},"canonical_sha256":"eba23e854f644faa0d4afdff5a89612b9ae604e6f7fbc2aad0083c5f56f3f0ab","source":{"kind":"arxiv","id":"2010.08819","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.08819","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"arxiv_version","alias_value":"2010.08819v1","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.08819","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"pith_short_12","alias_value":"5ORD5BKPMRH2","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"pith_short_16","alias_value":"5ORD5BKPMRH2UDKK","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"pith_short_8","alias_value":"5ORD5BKP","created_at":"2026-07-05T01:43:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:5ORD5BKPMRH2UDKK7X7VVCLBFO","target":"record","payload":{"canonical_record":{"source":{"id":"2010.08819","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-17T16:20:33Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"81e1c0d1e45159f6509b2d794640941c62789f18634040f018e2f2025888d8f5","abstract_canon_sha256":"7de556b84d776fa9db3984fb07baf48b58ae5023287a70a2c7baad242fda17ca"},"schema_version":"1.0"},"canonical_sha256":"eba23e854f644faa0d4afdff5a89612b9ae604e6f7fbc2aad0083c5f56f3f0ab","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:43:45.718206Z","signature_b64":"4GNSrykuQ9J6oErYG8z3gEcl5XVDnLLhUsKyipI6NkrDJ0TxBROTJTlxWmowk3GP1XBH+Qlar4aZHQYm5xcvAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eba23e854f644faa0d4afdff5a89612b9ae604e6f7fbc2aad0083c5f56f3f0ab","last_reissued_at":"2026-07-05T01:43:45.717808Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:43:45.717808Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.08819","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:43:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mZcay6TYwN5qL+thrCKsCzAHJZTexYIbH/CS7GaSiDT2eV0b9HIuKTDWMkAuYvgPtetn3Ppvjua9C7Xt8MI6Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T07:48:15.218018Z"},"content_sha256":"2ca574d18dd3dd89bccb9030a401f36a9a1442eacdfac05375c925baf12b5033","schema_version":"1.0","event_id":"sha256:2ca574d18dd3dd89bccb9030a401f36a9a1442eacdfac05375c925baf12b5033"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:5ORD5BKPMRH2UDKK7X7VVCLBFO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Assessment of Reward Functions in Reinforcement Learning for Multi-Modal Urban Traffic Control under Real-World limitations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.LG","authors_text":"Alvaro Cabrejas-Egea, Colm Connaughton","submitted_at":"2020-10-17T16:20:33Z","abstract_excerpt":"Reinforcement Learning is proving a successful tool that can manage urban intersections with a fraction of the effort required to curate traditional traffic controllers. However, literature on the introduction and control of pedestrians to such intersections is scarce. Furthermore, it is unclear what traffic state variables should be used as reward to obtain the best agent performance. This paper robustly evaluates 30 different Reinforcement Learning reward functions for controlling intersections serving pedestrians and vehicles covering the main traffic state variables available via modern vi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.08819","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/2010.08819/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":"2026-07-05T01:43:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5wFlFfOHaNs3Tclozgb7OVH5AfO+IhbioJm7mPOTyTSubtOyp5dDHJGZVtBI59XPIGyucHafPJaAuuIa1xDdDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T07:48:15.218401Z"},"content_sha256":"f8dd0b3cbe845d47265d536312f36e63d4c3a8011bb10ea1760f25f6c1ff4581","schema_version":"1.0","event_id":"sha256:f8dd0b3cbe845d47265d536312f36e63d4c3a8011bb10ea1760f25f6c1ff4581"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5ORD5BKPMRH2UDKK7X7VVCLBFO/bundle.json","state_url":"https://pith.science/pith/5ORD5BKPMRH2UDKK7X7VVCLBFO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5ORD5BKPMRH2UDKK7X7VVCLBFO/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":"2026-07-18T07:48:15Z","links":{"resolver":"https://pith.science/pith/5ORD5BKPMRH2UDKK7X7VVCLBFO","bundle":"https://pith.science/pith/5ORD5BKPMRH2UDKK7X7VVCLBFO/bundle.json","state":"https://pith.science/pith/5ORD5BKPMRH2UDKK7X7VVCLBFO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5ORD5BKPMRH2UDKK7X7VVCLBFO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:5ORD5BKPMRH2UDKK7X7VVCLBFO","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":"7de556b84d776fa9db3984fb07baf48b58ae5023287a70a2c7baad242fda17ca","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-17T16:20:33Z","title_canon_sha256":"81e1c0d1e45159f6509b2d794640941c62789f18634040f018e2f2025888d8f5"},"schema_version":"1.0","source":{"id":"2010.08819","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.08819","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"arxiv_version","alias_value":"2010.08819v1","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.08819","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"pith_short_12","alias_value":"5ORD5BKPMRH2","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"pith_short_16","alias_value":"5ORD5BKPMRH2UDKK","created_at":"2026-07-05T01:43:45Z"},{"alias_kind":"pith_short_8","alias_value":"5ORD5BKP","created_at":"2026-07-05T01:43:45Z"}],"graph_snapshots":[{"event_id":"sha256:f8dd0b3cbe845d47265d536312f36e63d4c3a8011bb10ea1760f25f6c1ff4581","target":"graph","created_at":"2026-07-05T01:43:45Z","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/2010.08819/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reinforcement Learning is proving a successful tool that can manage urban intersections with a fraction of the effort required to curate traditional traffic controllers. However, literature on the introduction and control of pedestrians to such intersections is scarce. Furthermore, it is unclear what traffic state variables should be used as reward to obtain the best agent performance. This paper robustly evaluates 30 different Reinforcement Learning reward functions for controlling intersections serving pedestrians and vehicles covering the main traffic state variables available via modern vi","authors_text":"Alvaro Cabrejas-Egea, Colm Connaughton","cross_cats":["cs.SY","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-17T16:20:33Z","title":"Assessment of Reward Functions in Reinforcement Learning for Multi-Modal Urban Traffic Control under Real-World limitations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.08819","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":"sha256:2ca574d18dd3dd89bccb9030a401f36a9a1442eacdfac05375c925baf12b5033","target":"record","created_at":"2026-07-05T01:43:45Z","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":"7de556b84d776fa9db3984fb07baf48b58ae5023287a70a2c7baad242fda17ca","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-17T16:20:33Z","title_canon_sha256":"81e1c0d1e45159f6509b2d794640941c62789f18634040f018e2f2025888d8f5"},"schema_version":"1.0","source":{"id":"2010.08819","kind":"arxiv","version":1}},"canonical_sha256":"eba23e854f644faa0d4afdff5a89612b9ae604e6f7fbc2aad0083c5f56f3f0ab","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eba23e854f644faa0d4afdff5a89612b9ae604e6f7fbc2aad0083c5f56f3f0ab","first_computed_at":"2026-07-05T01:43:45.717808Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:43:45.717808Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4GNSrykuQ9J6oErYG8z3gEcl5XVDnLLhUsKyipI6NkrDJ0TxBROTJTlxWmowk3GP1XBH+Qlar4aZHQYm5xcvAA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:43:45.718206Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.08819","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2ca574d18dd3dd89bccb9030a401f36a9a1442eacdfac05375c925baf12b5033","sha256:f8dd0b3cbe845d47265d536312f36e63d4c3a8011bb10ea1760f25f6c1ff4581"],"state_sha256":"4596a3853800bb3d57ccd46dbec8103bff27bd8fd2d595e4d213129bcfb3afe2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rYTszYauN0Vl8GPdLb2Q0tOoTtV9VawGxUvmvrQyb/8JGUf+hnaMU6IpeefBwFi8Pp1xI1V9rlOC4rRIvD5OAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-18T07:48:15.220979Z","bundle_sha256":"5f0e8043932939a3c1627158b285f668f29026de533dc8a61093104a361eb245"}}