{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:52IVNJFEYNFXJXCDO7CK67AWZD","short_pith_number":"pith:52IVNJFE","canonical_record":{"source":{"id":"1205.0986","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2012-05-04T15:32:43Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"81a4d73ff804003f3688bd50fc5561c5914f358f1d65494aa1cc843effc30f0d","abstract_canon_sha256":"a28dbfeba55d8fb241d2a81bbdd9e97a4c652a3ddfcec7412a51743de179d5a1"},"schema_version":"1.0"},"canonical_sha256":"ee9156a4a4c34b74dc4377c4af7c16c8cd40808cee4a6e5f5a4171ced3dedbf8","source":{"kind":"arxiv","id":"1205.0986","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1205.0986","created_at":"2026-05-18T03:56:23Z"},{"alias_kind":"arxiv_version","alias_value":"1205.0986v1","created_at":"2026-05-18T03:56:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.0986","created_at":"2026-05-18T03:56:23Z"},{"alias_kind":"pith_short_12","alias_value":"52IVNJFEYNFX","created_at":"2026-05-18T12:26:53Z"},{"alias_kind":"pith_short_16","alias_value":"52IVNJFEYNFXJXCD","created_at":"2026-05-18T12:26:53Z"},{"alias_kind":"pith_short_8","alias_value":"52IVNJFE","created_at":"2026-05-18T12:26:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:52IVNJFEYNFXJXCDO7CK67AWZD","target":"record","payload":{"canonical_record":{"source":{"id":"1205.0986","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2012-05-04T15:32:43Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"81a4d73ff804003f3688bd50fc5561c5914f358f1d65494aa1cc843effc30f0d","abstract_canon_sha256":"a28dbfeba55d8fb241d2a81bbdd9e97a4c652a3ddfcec7412a51743de179d5a1"},"schema_version":"1.0"},"canonical_sha256":"ee9156a4a4c34b74dc4377c4af7c16c8cd40808cee4a6e5f5a4171ced3dedbf8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:56:23.407206Z","signature_b64":"panByX53L//wpv6YtytOslVNz9YE+YXXR+wstSR7GQ7/qUDWfWSKkPc0QL6e2sQWUdEC16im5WLaPxuoVV3eCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee9156a4a4c34b74dc4377c4af7c16c8cd40808cee4a6e5f5a4171ced3dedbf8","last_reissued_at":"2026-05-18T03:56:23.406533Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:56:23.406533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1205.0986","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":"2026-05-18T03:56:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rThSlOguMB0ucru1DZfgdY24UF9ekP4rR3dbrNpGUgyHlc+/fOzIyRn7vpHVaSpnGfI5h/1+2xiYnxq9my7QCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T13:01:32.640530Z"},"content_sha256":"26915e44ce7879c22bc56dd91d7af73672c4b69c2e50a9d3908e04f4beaa09d8","schema_version":"1.0","event_id":"sha256:26915e44ce7879c22bc56dd91d7af73672c4b69c2e50a9d3908e04f4beaa09d8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:52IVNJFEYNFXJXCDO7CK67AWZD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robot Navigation using Reinforcement Learning and Slow Feature Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.AI","authors_text":"Wendelin B\\\"ohmer","submitted_at":"2012-05-04T15:32:43Z","abstract_excerpt":"The application of reinforcement learning algorithms onto real life problems always bears the challenge of filtering the environmental state out of raw sensor readings. While most approaches use heuristics, biology suggests that there must exist an unsupervised method to construct such filters automatically. Besides the extraction of environmental states, the filters have to represent them in a fashion that support modern reinforcement algorithms. Many popular algorithms use a linear architecture, so one should aim at filters that have good approximation properties in combination with linear f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.0986","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":""},"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":"2026-05-18T03:56:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q8tGvy6LVTFko7SZ2HzFXN9CmBIB7cKXNSLdrV/tOmjwBehbRdl7YMZ/ecHUwEz+CUfP7FBWamVvSHSVZm2JAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T13:01:32.640882Z"},"content_sha256":"c54b6eaf35b811bec46f36fdbb7078acfd08927fea6f369022ccfa1ecdd082d2","schema_version":"1.0","event_id":"sha256:c54b6eaf35b811bec46f36fdbb7078acfd08927fea6f369022ccfa1ecdd082d2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/52IVNJFEYNFXJXCDO7CK67AWZD/bundle.json","state_url":"https://pith.science/pith/52IVNJFEYNFXJXCDO7CK67AWZD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/52IVNJFEYNFXJXCDO7CK67AWZD/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":"2026-06-06T13:01:32Z","links":{"resolver":"https://pith.science/pith/52IVNJFEYNFXJXCDO7CK67AWZD","bundle":"https://pith.science/pith/52IVNJFEYNFXJXCDO7CK67AWZD/bundle.json","state":"https://pith.science/pith/52IVNJFEYNFXJXCDO7CK67AWZD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/52IVNJFEYNFXJXCDO7CK67AWZD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:52IVNJFEYNFXJXCDO7CK67AWZD","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":"a28dbfeba55d8fb241d2a81bbdd9e97a4c652a3ddfcec7412a51743de179d5a1","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2012-05-04T15:32:43Z","title_canon_sha256":"81a4d73ff804003f3688bd50fc5561c5914f358f1d65494aa1cc843effc30f0d"},"schema_version":"1.0","source":{"id":"1205.0986","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1205.0986","created_at":"2026-05-18T03:56:23Z"},{"alias_kind":"arxiv_version","alias_value":"1205.0986v1","created_at":"2026-05-18T03:56:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.0986","created_at":"2026-05-18T03:56:23Z"},{"alias_kind":"pith_short_12","alias_value":"52IVNJFEYNFX","created_at":"2026-05-18T12:26:53Z"},{"alias_kind":"pith_short_16","alias_value":"52IVNJFEYNFXJXCD","created_at":"2026-05-18T12:26:53Z"},{"alias_kind":"pith_short_8","alias_value":"52IVNJFE","created_at":"2026-05-18T12:26:53Z"}],"graph_snapshots":[{"event_id":"sha256:c54b6eaf35b811bec46f36fdbb7078acfd08927fea6f369022ccfa1ecdd082d2","target":"graph","created_at":"2026-05-18T03:56:23Z","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"},"paper":{"abstract_excerpt":"The application of reinforcement learning algorithms onto real life problems always bears the challenge of filtering the environmental state out of raw sensor readings. While most approaches use heuristics, biology suggests that there must exist an unsupervised method to construct such filters automatically. Besides the extraction of environmental states, the filters have to represent them in a fashion that support modern reinforcement algorithms. Many popular algorithms use a linear architecture, so one should aim at filters that have good approximation properties in combination with linear f","authors_text":"Wendelin B\\\"ohmer","cross_cats":["cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2012-05-04T15:32:43Z","title":"Robot Navigation using Reinforcement Learning and Slow Feature Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.0986","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":"sha256:26915e44ce7879c22bc56dd91d7af73672c4b69c2e50a9d3908e04f4beaa09d8","target":"record","created_at":"2026-05-18T03:56:23Z","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":"a28dbfeba55d8fb241d2a81bbdd9e97a4c652a3ddfcec7412a51743de179d5a1","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2012-05-04T15:32:43Z","title_canon_sha256":"81a4d73ff804003f3688bd50fc5561c5914f358f1d65494aa1cc843effc30f0d"},"schema_version":"1.0","source":{"id":"1205.0986","kind":"arxiv","version":1}},"canonical_sha256":"ee9156a4a4c34b74dc4377c4af7c16c8cd40808cee4a6e5f5a4171ced3dedbf8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ee9156a4a4c34b74dc4377c4af7c16c8cd40808cee4a6e5f5a4171ced3dedbf8","first_computed_at":"2026-05-18T03:56:23.406533Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:56:23.406533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"panByX53L//wpv6YtytOslVNz9YE+YXXR+wstSR7GQ7/qUDWfWSKkPc0QL6e2sQWUdEC16im5WLaPxuoVV3eCA==","signature_status":"signed_v1","signed_at":"2026-05-18T03:56:23.407206Z","signed_message":"canonical_sha256_bytes"},"source_id":"1205.0986","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:26915e44ce7879c22bc56dd91d7af73672c4b69c2e50a9d3908e04f4beaa09d8","sha256:c54b6eaf35b811bec46f36fdbb7078acfd08927fea6f369022ccfa1ecdd082d2"],"state_sha256":"42801ba5d687d11e80bb4d4440103adb42eda48e98ce987c4cefd9a801dae995"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K9ttQTb+lXRs6UEQHTFK3/llYtXltA3UOEeNRB+P3Td6m1oZ+dhf0HSCGY37DMvJJfkmmD5G2T5c84W7X7lAAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T13:01:32.643071Z","bundle_sha256":"bb1f1fa0d4720223c7b435f8b4683eac2a8cb37bcca1752aea4a27e23c3fd5d4"}}