{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:3T6OZNOPKIHX7SLL4CQFGVLGHZ","short_pith_number":"pith:3T6OZNOP","canonical_record":{"source":{"id":"2102.09812","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-19T09:00:29Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"b02db6f1943dc5c3547fbe549b2e730ee1301ccb75d70f83cee441e39abc820c","abstract_canon_sha256":"8df008cfe2b1b22e9750bdd7e49b1524853618c7305084291ffa4eb537c207b0"},"schema_version":"1.0"},"canonical_sha256":"dcfcecb5cf520f7fc96be0a05355663e77f34adc628cd31344111db486747c36","source":{"kind":"arxiv","id":"2102.09812","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.09812","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"arxiv_version","alias_value":"2102.09812v1","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.09812","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"pith_short_12","alias_value":"3T6OZNOPKIHX","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"pith_short_16","alias_value":"3T6OZNOPKIHX7SLL","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"pith_short_8","alias_value":"3T6OZNOP","created_at":"2026-07-05T02:16:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:3T6OZNOPKIHX7SLL4CQFGVLGHZ","target":"record","payload":{"canonical_record":{"source":{"id":"2102.09812","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-19T09:00:29Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"b02db6f1943dc5c3547fbe549b2e730ee1301ccb75d70f83cee441e39abc820c","abstract_canon_sha256":"8df008cfe2b1b22e9750bdd7e49b1524853618c7305084291ffa4eb537c207b0"},"schema_version":"1.0"},"canonical_sha256":"dcfcecb5cf520f7fc96be0a05355663e77f34adc628cd31344111db486747c36","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:16:31.166396Z","signature_b64":"sIg0J4ZxCQPZ8lEKRSjrXZplOazAWV9a2hHOgn8MF2D4wK9AFCRMGi6FEhXn6+3xbzQSk0rr1qx1PuCU/AwfDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dcfcecb5cf520f7fc96be0a05355663e77f34adc628cd31344111db486747c36","last_reissued_at":"2026-07-05T02:16:31.165979Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:16:31.165979Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2102.09812","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":"2026-07-05T02:16:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g4dXkq0PW8sX5xhjMun8+vz/RyuxmGqsW/TGJqLayLxhL1ybLUt9I6RBRaNB6I/KaAKKB2jn0MEqGi5QycRmAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T03:51:01.497154Z"},"content_sha256":"e96abd1ba18994fd5b499a991d6420a3d33cd19f90d918b35746266b9f7fe7c6","schema_version":"1.0","event_id":"sha256:e96abd1ba18994fd5b499a991d6420a3d33cd19f90d918b35746266b9f7fe7c6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:3T6OZNOPKIHX7SLL4CQFGVLGHZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.RO"],"primary_cat":"cs.LG","authors_text":"Daniela Rus, Igor Gilitschenski, Lucas Liebenwein, Ryan Sander, Sertac Karaman, Tim Seyde, Wilko Schwarting","submitted_at":"2021-02-19T09:00:29Z","abstract_excerpt":"Learning competitive behaviors in multi-agent settings such as racing requires long-term reasoning about potential adversarial interactions. This paper presents Deep Latent Competition (DLC), a novel reinforcement learning algorithm that learns competitive visual control policies through self-play in imagination. The DLC agent imagines multi-agent interaction sequences in the compact latent space of a learned world model that combines a joint transition function with opponent viewpoint prediction. Imagined self-play reduces costly sample generation in the real world, while the latent represent"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.09812","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/2102.09812/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":"2026-07-05T02:16:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FG+PO5bqerRpbH185CscVmw4Lq8R8WvPHev7MOQYv0/8PF0OcGSDZIPd7ujFfQq2X7ktNParDLuvX8+JvzpxCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T03:51:01.497543Z"},"content_sha256":"cb168af601523df8d4ba7f157b087ddcc7425ce2f4d7cef0e9c23f394f542eba","schema_version":"1.0","event_id":"sha256:cb168af601523df8d4ba7f157b087ddcc7425ce2f4d7cef0e9c23f394f542eba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3T6OZNOPKIHX7SLL4CQFGVLGHZ/bundle.json","state_url":"https://pith.science/pith/3T6OZNOPKIHX7SLL4CQFGVLGHZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3T6OZNOPKIHX7SLL4CQFGVLGHZ/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":"2026-07-27T03:51:01Z","links":{"resolver":"https://pith.science/pith/3T6OZNOPKIHX7SLL4CQFGVLGHZ","bundle":"https://pith.science/pith/3T6OZNOPKIHX7SLL4CQFGVLGHZ/bundle.json","state":"https://pith.science/pith/3T6OZNOPKIHX7SLL4CQFGVLGHZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3T6OZNOPKIHX7SLL4CQFGVLGHZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:3T6OZNOPKIHX7SLL4CQFGVLGHZ","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":"8df008cfe2b1b22e9750bdd7e49b1524853618c7305084291ffa4eb537c207b0","cross_cats_sorted":["cs.AI","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-19T09:00:29Z","title_canon_sha256":"b02db6f1943dc5c3547fbe549b2e730ee1301ccb75d70f83cee441e39abc820c"},"schema_version":"1.0","source":{"id":"2102.09812","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.09812","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"arxiv_version","alias_value":"2102.09812v1","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.09812","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"pith_short_12","alias_value":"3T6OZNOPKIHX","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"pith_short_16","alias_value":"3T6OZNOPKIHX7SLL","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"pith_short_8","alias_value":"3T6OZNOP","created_at":"2026-07-05T02:16:31Z"}],"graph_snapshots":[{"event_id":"sha256:cb168af601523df8d4ba7f157b087ddcc7425ce2f4d7cef0e9c23f394f542eba","target":"graph","created_at":"2026-07-05T02:16:31Z","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/2102.09812/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning competitive behaviors in multi-agent settings such as racing requires long-term reasoning about potential adversarial interactions. This paper presents Deep Latent Competition (DLC), a novel reinforcement learning algorithm that learns competitive visual control policies through self-play in imagination. The DLC agent imagines multi-agent interaction sequences in the compact latent space of a learned world model that combines a joint transition function with opponent viewpoint prediction. Imagined self-play reduces costly sample generation in the real world, while the latent represent","authors_text":"Daniela Rus, Igor Gilitschenski, Lucas Liebenwein, Ryan Sander, Sertac Karaman, Tim Seyde, Wilko Schwarting","cross_cats":["cs.AI","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-19T09:00:29Z","title":"Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.09812","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:e96abd1ba18994fd5b499a991d6420a3d33cd19f90d918b35746266b9f7fe7c6","target":"record","created_at":"2026-07-05T02:16:31Z","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":"8df008cfe2b1b22e9750bdd7e49b1524853618c7305084291ffa4eb537c207b0","cross_cats_sorted":["cs.AI","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-19T09:00:29Z","title_canon_sha256":"b02db6f1943dc5c3547fbe549b2e730ee1301ccb75d70f83cee441e39abc820c"},"schema_version":"1.0","source":{"id":"2102.09812","kind":"arxiv","version":1}},"canonical_sha256":"dcfcecb5cf520f7fc96be0a05355663e77f34adc628cd31344111db486747c36","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dcfcecb5cf520f7fc96be0a05355663e77f34adc628cd31344111db486747c36","first_computed_at":"2026-07-05T02:16:31.165979Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:16:31.165979Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sIg0J4ZxCQPZ8lEKRSjrXZplOazAWV9a2hHOgn8MF2D4wK9AFCRMGi6FEhXn6+3xbzQSk0rr1qx1PuCU/AwfDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:16:31.166396Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.09812","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e96abd1ba18994fd5b499a991d6420a3d33cd19f90d918b35746266b9f7fe7c6","sha256:cb168af601523df8d4ba7f157b087ddcc7425ce2f4d7cef0e9c23f394f542eba"],"state_sha256":"d4e7a0023fa091bf53a168f3e1788af88233b9a4a0a43cae606e54cf7da3e721"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ldtKCbfwln9I+DsNdFVmxg+haCZ3ruhc7USqhBoobV3nZk6D/Gdc2UBd8H7s+sKG0w8EP9XEmbjawsjA8xpUCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-27T03:51:01.500010Z","bundle_sha256":"aef849f54bd1b156e721a48a1a8b98c751a23be5cb33611a64f1615d54710b35"}}