{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:GE33UQC3XH7JL3S2QIXLEOOE47","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":"dd004cf3e69f3985fdff9386e6904a5b65a062ede8c1cd18560069758749205b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-07-16T21:10:27Z","title_canon_sha256":"8d4a1f5ef22347bfa1b9972676c153382179c3501aba813926ea5dc5cdd00d17"},"schema_version":"1.0","source":{"id":"2607.15459","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.15459","created_at":"2026-07-20T00:18:35Z"},{"alias_kind":"arxiv_version","alias_value":"2607.15459v1","created_at":"2026-07-20T00:18:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.15459","created_at":"2026-07-20T00:18:35Z"},{"alias_kind":"pith_short_12","alias_value":"GE33UQC3XH7J","created_at":"2026-07-20T00:18:35Z"},{"alias_kind":"pith_short_16","alias_value":"GE33UQC3XH7JL3S2","created_at":"2026-07-20T00:18:35Z"},{"alias_kind":"pith_short_8","alias_value":"GE33UQC3","created_at":"2026-07-20T00:18:35Z"}],"graph_snapshots":[{"event_id":"sha256:1b88f4a846d90a8bf9be00643b0daca74220c71cbacf080e0e482ae954d7fdd9","target":"graph","created_at":"2026-07-20T00:18:35Z","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/2607.15459/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A trained deep reinforcement learning policy is a black box, and we ask whether it can be made explainable by rewriting it as an executable logic program that reproduces its behaviour and that a person can read, a logic engine can run, and an optimizer can edit. We present a three-stage post-hoc transformation that extracts a frozen proximal policy optimization teacher, induces an ordered rule list from its decisions in the manner of classical relational learning, and emits the result as a Prolog program whose every decision is executed by an off-the-shelf logic engine; a subsequent expansion ","authors_text":"Eduardo C. Garrido-Merch\\'an","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-07-16T21:10:27Z","title":"From Black Box to Executable Logic: Explainable Reinforcement Learning through Prolog Expert Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.15459","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:fc33108c917370a2ee2d4aeecf7330a44645a29bdacc78c23096c3adefcca47f","target":"record","created_at":"2026-07-20T00:18:35Z","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":"dd004cf3e69f3985fdff9386e6904a5b65a062ede8c1cd18560069758749205b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-07-16T21:10:27Z","title_canon_sha256":"8d4a1f5ef22347bfa1b9972676c153382179c3501aba813926ea5dc5cdd00d17"},"schema_version":"1.0","source":{"id":"2607.15459","kind":"arxiv","version":1}},"canonical_sha256":"3137ba405bb9fe95ee5a822eb239c4e7e0501172760bee128d843898ace40d01","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3137ba405bb9fe95ee5a822eb239c4e7e0501172760bee128d843898ace40d01","first_computed_at":"2026-07-20T00:18:35.084382Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-20T00:18:35.084382Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7mN3HJSJhWq8dvbALvB8lX4kye7YuN1aMgVMCQpRpI0nCLC7Q2Uh36ZtMkYxzSbLRY3Cj4/6Z+BIpMglcMWoDA==","signature_status":"signed_v1","signed_at":"2026-07-20T00:18:35.085227Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.15459","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fc33108c917370a2ee2d4aeecf7330a44645a29bdacc78c23096c3adefcca47f","sha256:1b88f4a846d90a8bf9be00643b0daca74220c71cbacf080e0e482ae954d7fdd9"],"state_sha256":"975e0e4e8b0c4198ad691dee819b88f511ec439fb02bb0361e6c20324fb2d336"}