{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:IXJNPHPYPLINHTX6YH2PKOMO6E","short_pith_number":"pith:IXJNPHPY","canonical_record":{"source":{"id":"2202.12322","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-02-24T19:07:23Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"502f9407c1f79cb2c77888841c79cb3d858bddbafad9e990b32bc0cb5e8b0e5f","abstract_canon_sha256":"b527baa90d6d093fc524a64a49a39f2c065d70f68bb8dd6930e1a23109020bb2"},"schema_version":"1.0"},"canonical_sha256":"45d2d79df87ad0d3cefec1f4f5398ef12893a8cc45821ab0bbbee643cb336bdb","source":{"kind":"arxiv","id":"2202.12322","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.12322","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"arxiv_version","alias_value":"2202.12322v1","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.12322","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"pith_short_12","alias_value":"IXJNPHPYPLIN","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"pith_short_16","alias_value":"IXJNPHPYPLINHTX6","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"pith_short_8","alias_value":"IXJNPHPY","created_at":"2026-07-05T03:59:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:IXJNPHPYPLINHTX6YH2PKOMO6E","target":"record","payload":{"canonical_record":{"source":{"id":"2202.12322","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-02-24T19:07:23Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"502f9407c1f79cb2c77888841c79cb3d858bddbafad9e990b32bc0cb5e8b0e5f","abstract_canon_sha256":"b527baa90d6d093fc524a64a49a39f2c065d70f68bb8dd6930e1a23109020bb2"},"schema_version":"1.0"},"canonical_sha256":"45d2d79df87ad0d3cefec1f4f5398ef12893a8cc45821ab0bbbee643cb336bdb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:59:54.134694Z","signature_b64":"m/BRj+CsCSSV5YFe9PnUFXznCkDc8t4aKHKduYj5+QANivCmgvSZLA2+OznIxm2RVrA19tB7CJ49jYKKHBejBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"45d2d79df87ad0d3cefec1f4f5398ef12893a8cc45821ab0bbbee643cb336bdb","last_reissued_at":"2026-07-05T03:59:54.134226Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:59:54.134226Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.12322","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":"2026-07-05T03:59:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cuDbRY9tIX0XmBYiCx5w/f5/HVfgatoMOcLfKEasQsTDlHoyfaiJSyw3tzz43N8WsYJo4gzSujjvuMZUo6SzBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:44:22.923360Z"},"content_sha256":"5104957878f738d58a24cb87325290a39c258f359b544e00a5e8eb6b8d37590d","schema_version":"1.0","event_id":"sha256:5104957878f738d58a24cb87325290a39c258f359b544e00a5e8eb6b8d37590d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:IXJNPHPYPLINHTX6YH2PKOMO6E","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evolving-to-Learn Reinforcement Learning Tasks with Spiking Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.NE","authors_text":"G. C. H. E. de Croon, J. J. Hagenaars, J. Lu","submitted_at":"2022-02-24T19:07:23Z","abstract_excerpt":"Inspired by the natural nervous system, synaptic plasticity rules are applied to train spiking neural networks with local information, making them suitable for online learning on neuromorphic hardware. However, when such rules are implemented to learn different new tasks, they usually require a significant amount of work on task-dependent fine-tuning. This paper aims to make this process easier by employing an evolutionary algorithm that evolves suitable synaptic plasticity rules for the task at hand. More specifically, we provide a set of various local signals, a set of mathematical operators"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.12322","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/2202.12322/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":"2026-07-05T03:59:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W+W/H5spfoFN+7pSelrEiv1U/Ddi4tDNyu8u/7i6nYVnCsn7WqwhJXLgBvaLy3kySLq4YVRET8UbPLCDY0SmBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:44:22.923765Z"},"content_sha256":"72819e42c1f525f283d7edbc0974b29021bd1300bb1d36f7cc4b961463d61b58","schema_version":"1.0","event_id":"sha256:72819e42c1f525f283d7edbc0974b29021bd1300bb1d36f7cc4b961463d61b58"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IXJNPHPYPLINHTX6YH2PKOMO6E/bundle.json","state_url":"https://pith.science/pith/IXJNPHPYPLINHTX6YH2PKOMO6E/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IXJNPHPYPLINHTX6YH2PKOMO6E/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":"2026-07-06T18:44:22Z","links":{"resolver":"https://pith.science/pith/IXJNPHPYPLINHTX6YH2PKOMO6E","bundle":"https://pith.science/pith/IXJNPHPYPLINHTX6YH2PKOMO6E/bundle.json","state":"https://pith.science/pith/IXJNPHPYPLINHTX6YH2PKOMO6E/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IXJNPHPYPLINHTX6YH2PKOMO6E/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:IXJNPHPYPLINHTX6YH2PKOMO6E","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":"b527baa90d6d093fc524a64a49a39f2c065d70f68bb8dd6930e1a23109020bb2","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-02-24T19:07:23Z","title_canon_sha256":"502f9407c1f79cb2c77888841c79cb3d858bddbafad9e990b32bc0cb5e8b0e5f"},"schema_version":"1.0","source":{"id":"2202.12322","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.12322","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"arxiv_version","alias_value":"2202.12322v1","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.12322","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"pith_short_12","alias_value":"IXJNPHPYPLIN","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"pith_short_16","alias_value":"IXJNPHPYPLINHTX6","created_at":"2026-07-05T03:59:54Z"},{"alias_kind":"pith_short_8","alias_value":"IXJNPHPY","created_at":"2026-07-05T03:59:54Z"}],"graph_snapshots":[{"event_id":"sha256:72819e42c1f525f283d7edbc0974b29021bd1300bb1d36f7cc4b961463d61b58","target":"graph","created_at":"2026-07-05T03:59:54Z","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/2202.12322/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Inspired by the natural nervous system, synaptic plasticity rules are applied to train spiking neural networks with local information, making them suitable for online learning on neuromorphic hardware. However, when such rules are implemented to learn different new tasks, they usually require a significant amount of work on task-dependent fine-tuning. This paper aims to make this process easier by employing an evolutionary algorithm that evolves suitable synaptic plasticity rules for the task at hand. More specifically, we provide a set of various local signals, a set of mathematical operators","authors_text":"G. C. H. E. de Croon, J. J. Hagenaars, J. Lu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-02-24T19:07:23Z","title":"Evolving-to-Learn Reinforcement Learning Tasks with Spiking Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.12322","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":"sha256:5104957878f738d58a24cb87325290a39c258f359b544e00a5e8eb6b8d37590d","target":"record","created_at":"2026-07-05T03:59:54Z","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":"b527baa90d6d093fc524a64a49a39f2c065d70f68bb8dd6930e1a23109020bb2","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-02-24T19:07:23Z","title_canon_sha256":"502f9407c1f79cb2c77888841c79cb3d858bddbafad9e990b32bc0cb5e8b0e5f"},"schema_version":"1.0","source":{"id":"2202.12322","kind":"arxiv","version":1}},"canonical_sha256":"45d2d79df87ad0d3cefec1f4f5398ef12893a8cc45821ab0bbbee643cb336bdb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"45d2d79df87ad0d3cefec1f4f5398ef12893a8cc45821ab0bbbee643cb336bdb","first_computed_at":"2026-07-05T03:59:54.134226Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:59:54.134226Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"m/BRj+CsCSSV5YFe9PnUFXznCkDc8t4aKHKduYj5+QANivCmgvSZLA2+OznIxm2RVrA19tB7CJ49jYKKHBejBA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:59:54.134694Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.12322","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5104957878f738d58a24cb87325290a39c258f359b544e00a5e8eb6b8d37590d","sha256:72819e42c1f525f283d7edbc0974b29021bd1300bb1d36f7cc4b961463d61b58"],"state_sha256":"d89aa541e99fe19dbc0fc0886a73cb48840d6bfaee8e83c85682a0a6ae5f86c8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6poFfXhwx+9G9GToKB/7vLMbpN+PP7BSzx7UrObO6YnaMYR6ddK0Ejits73S3TbQKgTRHdT34BQ6Cb0ASQtzAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:44:22.925691Z","bundle_sha256":"54e1fae77e727ecafa2be45342414a1086dff725be8afbd90794e17c5027f12d"}}