{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:BAARVAFEJXFP5O67MVT6LNN34C","short_pith_number":"pith:BAARVAFE","schema_version":"1.0","canonical_sha256":"08011a80a44dcafebbdf6567e5b5bbe0a0708b162a4bc1bf1ebdef7f71a4de7d","source":{"kind":"arxiv","id":"2307.08933","version":1},"attestation_state":"computed","paper":{"title":"IxDRL: A Novel Explainable Deep Reinforcement Learning Toolkit based on Analyses of Interestingness","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC","cs.LG"],"primary_cat":"cs.AI","authors_text":"Melinda Gervasio, Pedro Sequeira","submitted_at":"2023-07-18T02:43:19Z","abstract_excerpt":"In recent years, advances in deep learning have resulted in a plethora of successes in the use of reinforcement learning (RL) to solve complex sequential decision tasks with high-dimensional inputs. However, existing systems lack the necessary mechanisms to provide humans with a holistic view of their competence, presenting an impediment to their adoption, particularly in critical applications where the decisions an agent makes can have significant consequences. Yet, existing RL-based systems are essentially competency-unaware in that they lack the necessary interpretation mechanisms to allow "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2307.08933","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-07-18T02:43:19Z","cross_cats_sorted":["cs.HC","cs.LG"],"title_canon_sha256":"8183c5d1840ad68b9380749ee9b45d6a29458b9e94c454c3a070fb5f2fe2e27b","abstract_canon_sha256":"b7f5ad8464856c847c0d6f093a75173ec3bb8f8bdb3982b8ae1ef4d6b33aa3c4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:31:36.225774Z","signature_b64":"PZ+0tGkpsMQkVvYfzSt7o/MreP9F7HewCPsfJhVbwqlcIqngHSPWnzxzxM5LCi7ZPPSb3IHnr8IS1RhyZCK2DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08011a80a44dcafebbdf6567e5b5bbe0a0708b162a4bc1bf1ebdef7f71a4de7d","last_reissued_at":"2026-07-05T06:31:36.225261Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:31:36.225261Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"IxDRL: A Novel Explainable Deep Reinforcement Learning Toolkit based on Analyses of Interestingness","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC","cs.LG"],"primary_cat":"cs.AI","authors_text":"Melinda Gervasio, Pedro Sequeira","submitted_at":"2023-07-18T02:43:19Z","abstract_excerpt":"In recent years, advances in deep learning have resulted in a plethora of successes in the use of reinforcement learning (RL) to solve complex sequential decision tasks with high-dimensional inputs. However, existing systems lack the necessary mechanisms to provide humans with a holistic view of their competence, presenting an impediment to their adoption, particularly in critical applications where the decisions an agent makes can have significant consequences. Yet, existing RL-based systems are essentially competency-unaware in that they lack the necessary interpretation mechanisms to allow "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.08933","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/2307.08933/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2307.08933","created_at":"2026-07-05T06:31:36.225324+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.08933v1","created_at":"2026-07-05T06:31:36.225324+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.08933","created_at":"2026-07-05T06:31:36.225324+00:00"},{"alias_kind":"pith_short_12","alias_value":"BAARVAFEJXFP","created_at":"2026-07-05T06:31:36.225324+00:00"},{"alias_kind":"pith_short_16","alias_value":"BAARVAFEJXFP5O67","created_at":"2026-07-05T06:31:36.225324+00:00"},{"alias_kind":"pith_short_8","alias_value":"BAARVAFE","created_at":"2026-07-05T06:31:36.225324+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BAARVAFEJXFP5O67MVT6LNN34C","json":"https://pith.science/pith/BAARVAFEJXFP5O67MVT6LNN34C.json","graph_json":"https://pith.science/api/pith-number/BAARVAFEJXFP5O67MVT6LNN34C/graph.json","events_json":"https://pith.science/api/pith-number/BAARVAFEJXFP5O67MVT6LNN34C/events.json","paper":"https://pith.science/paper/BAARVAFE"},"agent_actions":{"view_html":"https://pith.science/pith/BAARVAFEJXFP5O67MVT6LNN34C","download_json":"https://pith.science/pith/BAARVAFEJXFP5O67MVT6LNN34C.json","view_paper":"https://pith.science/paper/BAARVAFE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.08933&json=true","fetch_graph":"https://pith.science/api/pith-number/BAARVAFEJXFP5O67MVT6LNN34C/graph.json","fetch_events":"https://pith.science/api/pith-number/BAARVAFEJXFP5O67MVT6LNN34C/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BAARVAFEJXFP5O67MVT6LNN34C/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BAARVAFEJXFP5O67MVT6LNN34C/action/storage_attestation","attest_author":"https://pith.science/pith/BAARVAFEJXFP5O67MVT6LNN34C/action/author_attestation","sign_citation":"https://pith.science/pith/BAARVAFEJXFP5O67MVT6LNN34C/action/citation_signature","submit_replication":"https://pith.science/pith/BAARVAFEJXFP5O67MVT6LNN34C/action/replication_record"}},"created_at":"2026-07-05T06:31:36.225324+00:00","updated_at":"2026-07-05T06:31:36.225324+00:00"}