{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:QZ7P233KCYJFKKZZNPVCGYQZLY","short_pith_number":"pith:QZ7P233K","canonical_record":{"source":{"id":"1701.04663","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-01-17T13:24:37Z","cross_cats_sorted":[],"title_canon_sha256":"9ac1083a10f90ecf54256b0ae32680b1c881ffbf6b5678a258b9ab7dee4307df","abstract_canon_sha256":"2e8cfb4b6ebc014127b3ec789f20db1200fe1350f2b603ad2e48e5ef976c8830"},"schema_version":"1.0"},"canonical_sha256":"867efd6f6a1612552b396bea2362195e2d13d6363da5ecee68ee30dd860821de","source":{"kind":"arxiv","id":"1701.04663","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1701.04663","created_at":"2026-05-18T00:52:42Z"},{"alias_kind":"arxiv_version","alias_value":"1701.04663v1","created_at":"2026-05-18T00:52:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.04663","created_at":"2026-05-18T00:52:42Z"},{"alias_kind":"pith_short_12","alias_value":"QZ7P233KCYJF","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_16","alias_value":"QZ7P233KCYJFKKZZ","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_8","alias_value":"QZ7P233K","created_at":"2026-05-18T12:31:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:QZ7P233KCYJFKKZZNPVCGYQZLY","target":"record","payload":{"canonical_record":{"source":{"id":"1701.04663","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-01-17T13:24:37Z","cross_cats_sorted":[],"title_canon_sha256":"9ac1083a10f90ecf54256b0ae32680b1c881ffbf6b5678a258b9ab7dee4307df","abstract_canon_sha256":"2e8cfb4b6ebc014127b3ec789f20db1200fe1350f2b603ad2e48e5ef976c8830"},"schema_version":"1.0"},"canonical_sha256":"867efd6f6a1612552b396bea2362195e2d13d6363da5ecee68ee30dd860821de","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:42.964026Z","signature_b64":"wUE5o3uaXqVKpar6rlwj0O73KDOYsv/KM3V6eysW1XUec5IwDLwiIJW8docZQw+l0K+JLCQoBw1BPkG7Ky74Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"867efd6f6a1612552b396bea2362195e2d13d6363da5ecee68ee30dd860821de","last_reissued_at":"2026-05-18T00:52:42.963409Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:42.963409Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1701.04663","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":"2026-05-18T00:52:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vM5Sphu/MrsDK7OHD1XtRvUPht2O+5XKlYCs4MH2RNtFMjFxJOVZea2wOv2LTy3cDkoZbki+xdZ56/7TYQv8Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T08:29:48.519073Z"},"content_sha256":"d1d8b6fcae8a4d1ade7e6b1bacec1f99faf55994c717befb18cc2eedd89345bc","schema_version":"1.0","event_id":"sha256:d1d8b6fcae8a4d1ade7e6b1bacec1f99faf55994c717befb18cc2eedd89345bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:QZ7P233KCYJFKKZZNPVCGYQZLY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Intrinsically Motivated Acquisition of Modular Slow Features for Humanoids in Continuous and Non-Stationary Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Laurenz Wiskott, Varun Raj Kompella","submitted_at":"2017-01-17T13:24:37Z","abstract_excerpt":"A compact information-rich representation of the environment, also called a feature abstraction, can simplify a robot's task of mapping its raw sensory inputs to useful action sequences. However, in environments that are non-stationary and only partially observable, a single abstraction is probably not sufficient to encode most variations. Therefore, learning multiple sets of spatially or temporally local, modular abstractions of the inputs would be beneficial. How can a robot learn these local abstractions without a teacher? More specifically, how can it decide from where and when to start le"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.04663","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":"2026-05-18T00:52:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r70kUzwZWyQneQ8oIReg7XQzXPlQtccBg+ChVUEOeAp7QIOJnaiutgpusHJFK7X+aKUCSwszfzvE3xrXZ1WaAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T08:29:48.519720Z"},"content_sha256":"5042b9938adc4caa5b82bad3a5fafce4a114d5990ba7dbd1db7685e4dbcc8cdd","schema_version":"1.0","event_id":"sha256:5042b9938adc4caa5b82bad3a5fafce4a114d5990ba7dbd1db7685e4dbcc8cdd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QZ7P233KCYJFKKZZNPVCGYQZLY/bundle.json","state_url":"https://pith.science/pith/QZ7P233KCYJFKKZZNPVCGYQZLY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QZ7P233KCYJFKKZZNPVCGYQZLY/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":"2026-06-11T08:29:48Z","links":{"resolver":"https://pith.science/pith/QZ7P233KCYJFKKZZNPVCGYQZLY","bundle":"https://pith.science/pith/QZ7P233KCYJFKKZZNPVCGYQZLY/bundle.json","state":"https://pith.science/pith/QZ7P233KCYJFKKZZNPVCGYQZLY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QZ7P233KCYJFKKZZNPVCGYQZLY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:QZ7P233KCYJFKKZZNPVCGYQZLY","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":"2e8cfb4b6ebc014127b3ec789f20db1200fe1350f2b603ad2e48e5ef976c8830","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-01-17T13:24:37Z","title_canon_sha256":"9ac1083a10f90ecf54256b0ae32680b1c881ffbf6b5678a258b9ab7dee4307df"},"schema_version":"1.0","source":{"id":"1701.04663","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1701.04663","created_at":"2026-05-18T00:52:42Z"},{"alias_kind":"arxiv_version","alias_value":"1701.04663v1","created_at":"2026-05-18T00:52:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.04663","created_at":"2026-05-18T00:52:42Z"},{"alias_kind":"pith_short_12","alias_value":"QZ7P233KCYJF","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_16","alias_value":"QZ7P233KCYJFKKZZ","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_8","alias_value":"QZ7P233K","created_at":"2026-05-18T12:31:39Z"}],"graph_snapshots":[{"event_id":"sha256:5042b9938adc4caa5b82bad3a5fafce4a114d5990ba7dbd1db7685e4dbcc8cdd","target":"graph","created_at":"2026-05-18T00:52:42Z","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":"A compact information-rich representation of the environment, also called a feature abstraction, can simplify a robot's task of mapping its raw sensory inputs to useful action sequences. However, in environments that are non-stationary and only partially observable, a single abstraction is probably not sufficient to encode most variations. Therefore, learning multiple sets of spatially or temporally local, modular abstractions of the inputs would be beneficial. How can a robot learn these local abstractions without a teacher? More specifically, how can it decide from where and when to start le","authors_text":"Laurenz Wiskott, Varun Raj Kompella","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-01-17T13:24:37Z","title":"Intrinsically Motivated Acquisition of Modular Slow Features for Humanoids in Continuous and Non-Stationary Environments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.04663","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:d1d8b6fcae8a4d1ade7e6b1bacec1f99faf55994c717befb18cc2eedd89345bc","target":"record","created_at":"2026-05-18T00:52:42Z","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":"2e8cfb4b6ebc014127b3ec789f20db1200fe1350f2b603ad2e48e5ef976c8830","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-01-17T13:24:37Z","title_canon_sha256":"9ac1083a10f90ecf54256b0ae32680b1c881ffbf6b5678a258b9ab7dee4307df"},"schema_version":"1.0","source":{"id":"1701.04663","kind":"arxiv","version":1}},"canonical_sha256":"867efd6f6a1612552b396bea2362195e2d13d6363da5ecee68ee30dd860821de","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"867efd6f6a1612552b396bea2362195e2d13d6363da5ecee68ee30dd860821de","first_computed_at":"2026-05-18T00:52:42.963409Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:52:42.963409Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wUE5o3uaXqVKpar6rlwj0O73KDOYsv/KM3V6eysW1XUec5IwDLwiIJW8docZQw+l0K+JLCQoBw1BPkG7Ky74Dw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:52:42.964026Z","signed_message":"canonical_sha256_bytes"},"source_id":"1701.04663","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d1d8b6fcae8a4d1ade7e6b1bacec1f99faf55994c717befb18cc2eedd89345bc","sha256:5042b9938adc4caa5b82bad3a5fafce4a114d5990ba7dbd1db7685e4dbcc8cdd"],"state_sha256":"615f7df6d44091fd7431b0f45d5f8c9f8028c56a364c2778b644857ce2e1ac97"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9xGAcUY5rJkFQfxCEQ66mWzk4d4hExizrpqFZaSjyHOFn1s2BkzX3mDY0qKXuq+QmvIhdtYQps8AIt5/NjANBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T08:29:48.523753Z","bundle_sha256":"7a7a85887bdb930d976d6f5130ed7abf5092a872d44562b59b1247d7e347933a"}}