{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:6LJRM2RNNJ422MS7DIQAZRQXQM","short_pith_number":"pith:6LJRM2RN","canonical_record":{"source":{"id":"2109.04155","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-09-09T10:33:36Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"86d5ff02388f31f2858ccc9890f967c1a40462bd60516293f1ebe00d5b48db59","abstract_canon_sha256":"80ad56527e6204dc045440a5d3899ad2b736e749b2a01401932d9c3361df9aa1"},"schema_version":"1.0"},"canonical_sha256":"f2d3166a2d6a79ad325f1a200cc617830dcc50d26ce208a1fde4c7f298525a4f","source":{"kind":"arxiv","id":"2109.04155","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.04155","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"arxiv_version","alias_value":"2109.04155v1","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.04155","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"pith_short_12","alias_value":"6LJRM2RNNJ42","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"pith_short_16","alias_value":"6LJRM2RNNJ422MS7","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"pith_short_8","alias_value":"6LJRM2RN","created_at":"2026-07-05T03:12:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:6LJRM2RNNJ422MS7DIQAZRQXQM","target":"record","payload":{"canonical_record":{"source":{"id":"2109.04155","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-09-09T10:33:36Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"86d5ff02388f31f2858ccc9890f967c1a40462bd60516293f1ebe00d5b48db59","abstract_canon_sha256":"80ad56527e6204dc045440a5d3899ad2b736e749b2a01401932d9c3361df9aa1"},"schema_version":"1.0"},"canonical_sha256":"f2d3166a2d6a79ad325f1a200cc617830dcc50d26ce208a1fde4c7f298525a4f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:12:55.719218Z","signature_b64":"Wjy+Pk+vgDAYr4lfoTaEyRdg5ajSXAgKQB/YMhFnSYc0oLKiuOhuavSAFpDCBo5r20jQsbCay64sQhrs6N/IAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f2d3166a2d6a79ad325f1a200cc617830dcc50d26ce208a1fde4c7f298525a4f","last_reissued_at":"2026-07-05T03:12:55.718871Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:12:55.718871Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2109.04155","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":"2026-07-05T03:12:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4Jj5s16nMf6xyiJGViTMLrOQ1cWxEbFamIwBD/WQZnicg5erOHnHQ1JQmFG/wXCWs2D3ly6lOyBj4ih3RqEYCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T08:22:02.315435Z"},"content_sha256":"4eba8c84352a53868b4fc7f2cb98543ebf9c00adbf3e65fbbe84fcd82e6d7b5d","schema_version":"1.0","event_id":"sha256:4eba8c84352a53868b4fc7f2cb98543ebf9c00adbf3e65fbbe84fcd82e6d7b5d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:6LJRM2RNNJ422MS7DIQAZRQXQM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.AI","authors_text":"Niels van Hoeffelen, Pablo Lanillos","submitted_at":"2021-09-09T10:33:36Z","abstract_excerpt":"Despite the potential of active inference for visual-based control, learning the model and the preferences (priors) while interacting with the environment is challenging. Here, we study the performance of a deep active inference (dAIF) agent on OpenAI's car racing benchmark, where there is no access to the car's state. The agent learns to encode the world's state from high-dimensional input through unsupervised representation learning. State inference and control are learned end-to-end by optimizing the expected free energy. Results show that our model achieves comparable performance to deep Q"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.04155","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/2109.04155/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":"2026-07-05T03:12:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4kDAUJ1Rr0wUGYcHKW4NBNfAW7bEn8aDz3uZh27AafZ2t+7ETVlSEJhn/sYD4M1aFoaC7pc+fDPmLEkA96lYDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T08:22:02.315799Z"},"content_sha256":"4337a69d2b81b1ce6f15c3bdadb3567a85c1df8e6216498604f5c3c87a4be33f","schema_version":"1.0","event_id":"sha256:4337a69d2b81b1ce6f15c3bdadb3567a85c1df8e6216498604f5c3c87a4be33f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6LJRM2RNNJ422MS7DIQAZRQXQM/bundle.json","state_url":"https://pith.science/pith/6LJRM2RNNJ422MS7DIQAZRQXQM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6LJRM2RNNJ422MS7DIQAZRQXQM/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":"2026-07-07T08:22:02Z","links":{"resolver":"https://pith.science/pith/6LJRM2RNNJ422MS7DIQAZRQXQM","bundle":"https://pith.science/pith/6LJRM2RNNJ422MS7DIQAZRQXQM/bundle.json","state":"https://pith.science/pith/6LJRM2RNNJ422MS7DIQAZRQXQM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6LJRM2RNNJ422MS7DIQAZRQXQM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:6LJRM2RNNJ422MS7DIQAZRQXQM","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":"80ad56527e6204dc045440a5d3899ad2b736e749b2a01401932d9c3361df9aa1","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-09-09T10:33:36Z","title_canon_sha256":"86d5ff02388f31f2858ccc9890f967c1a40462bd60516293f1ebe00d5b48db59"},"schema_version":"1.0","source":{"id":"2109.04155","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.04155","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"arxiv_version","alias_value":"2109.04155v1","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.04155","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"pith_short_12","alias_value":"6LJRM2RNNJ42","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"pith_short_16","alias_value":"6LJRM2RNNJ422MS7","created_at":"2026-07-05T03:12:55Z"},{"alias_kind":"pith_short_8","alias_value":"6LJRM2RN","created_at":"2026-07-05T03:12:55Z"}],"graph_snapshots":[{"event_id":"sha256:4337a69d2b81b1ce6f15c3bdadb3567a85c1df8e6216498604f5c3c87a4be33f","target":"graph","created_at":"2026-07-05T03:12:55Z","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/2109.04155/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite the potential of active inference for visual-based control, learning the model and the preferences (priors) while interacting with the environment is challenging. Here, we study the performance of a deep active inference (dAIF) agent on OpenAI's car racing benchmark, where there is no access to the car's state. The agent learns to encode the world's state from high-dimensional input through unsupervised representation learning. State inference and control are learned end-to-end by optimizing the expected free energy. Results show that our model achieves comparable performance to deep Q","authors_text":"Niels van Hoeffelen, Pablo Lanillos","cross_cats":["cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-09-09T10:33:36Z","title":"Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.04155","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":"sha256:4eba8c84352a53868b4fc7f2cb98543ebf9c00adbf3e65fbbe84fcd82e6d7b5d","target":"record","created_at":"2026-07-05T03:12:55Z","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":"80ad56527e6204dc045440a5d3899ad2b736e749b2a01401932d9c3361df9aa1","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-09-09T10:33:36Z","title_canon_sha256":"86d5ff02388f31f2858ccc9890f967c1a40462bd60516293f1ebe00d5b48db59"},"schema_version":"1.0","source":{"id":"2109.04155","kind":"arxiv","version":1}},"canonical_sha256":"f2d3166a2d6a79ad325f1a200cc617830dcc50d26ce208a1fde4c7f298525a4f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f2d3166a2d6a79ad325f1a200cc617830dcc50d26ce208a1fde4c7f298525a4f","first_computed_at":"2026-07-05T03:12:55.718871Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:12:55.718871Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Wjy+Pk+vgDAYr4lfoTaEyRdg5ajSXAgKQB/YMhFnSYc0oLKiuOhuavSAFpDCBo5r20jQsbCay64sQhrs6N/IAg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:12:55.719218Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.04155","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4eba8c84352a53868b4fc7f2cb98543ebf9c00adbf3e65fbbe84fcd82e6d7b5d","sha256:4337a69d2b81b1ce6f15c3bdadb3567a85c1df8e6216498604f5c3c87a4be33f"],"state_sha256":"980e7b490f3630e61d470b9ff46d94549d3901467c7e4d9f7ee62b50fe64623f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vj40WgjGUe6lZ/j+Er95rsWhcnQAAqCAwJBfU8B7lKhpzPwqnVmIALpWlaQ1gcePtAFTVbt3yEinOYHpyII1Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T08:22:02.317725Z","bundle_sha256":"3f94bef179417ba094e41e03ddf70387b5d581f5cfd0b0e87ea7dc4231b1a289"}}