{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:N7TSJFNJM3KH5STMCZFL2RUSGF","short_pith_number":"pith:N7TSJFNJ","schema_version":"1.0","canonical_sha256":"6fe72495a966d47eca6c164abd46923146d108c5458e97899b63973c4bf7f8e1","source":{"kind":"arxiv","id":"1605.03142","version":1},"attestation_state":"computed","paper":{"title":"Self-Modification of Policy and Utility Function in Rational Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Daniel Filan, Marcus Hutter, Mayank Daswani, Tom Everitt","submitted_at":"2016-05-10T18:25:49Z","abstract_excerpt":"Any agent that is part of the environment it interacts with and has versatile actuators (such as arms and fingers), will in principle have the ability to self-modify -- for example by changing its own source code. As we continue to create more and more intelligent agents, chances increase that they will learn about this ability. The question is: will they want to use it? For example, highly intelligent systems may find ways to change their goals to something more easily achievable, thereby `escaping' the control of their designers. In an important paper, Omohundro (2008) argued that goal prese"},"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":"1605.03142","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2016-05-10T18:25:49Z","cross_cats_sorted":[],"title_canon_sha256":"683190400a6cf17e361ea748fabbebfd96b1da6631f46fb6732acb2a7a3a337b","abstract_canon_sha256":"37dd7ac8cf8e040d951264d0e04023bfb7ab8f3906b52621acbf35f2e58ad883"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:15:07.449470Z","signature_b64":"AWJDR5yipEnPc4ZvFp2JJKL7btVGFu10sQ5T3MMcNETrhr3aCyrKctLas90dvj09p5qA055drNrwKHYIgV0GDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6fe72495a966d47eca6c164abd46923146d108c5458e97899b63973c4bf7f8e1","last_reissued_at":"2026-05-18T01:15:07.448299Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:15:07.448299Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Self-Modification of Policy and Utility Function in Rational Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Daniel Filan, Marcus Hutter, Mayank Daswani, Tom Everitt","submitted_at":"2016-05-10T18:25:49Z","abstract_excerpt":"Any agent that is part of the environment it interacts with and has versatile actuators (such as arms and fingers), will in principle have the ability to self-modify -- for example by changing its own source code. As we continue to create more and more intelligent agents, chances increase that they will learn about this ability. The question is: will they want to use it? For example, highly intelligent systems may find ways to change their goals to something more easily achievable, thereby `escaping' the control of their designers. In an important paper, Omohundro (2008) argued that goal prese"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.03142","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1605.03142","created_at":"2026-05-18T01:15:07.448621+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.03142v1","created_at":"2026-05-18T01:15:07.448621+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.03142","created_at":"2026-05-18T01:15:07.448621+00:00"},{"alias_kind":"pith_short_12","alias_value":"N7TSJFNJM3KH","created_at":"2026-05-18T12:30:32.724797+00:00"},{"alias_kind":"pith_short_16","alias_value":"N7TSJFNJM3KH5STM","created_at":"2026-05-18T12:30:32.724797+00:00"},{"alias_kind":"pith_short_8","alias_value":"N7TSJFNJ","created_at":"2026-05-18T12:30:32.724797+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"1606.06565","citing_title":"Concrete Problems in AI Safety","ref_index":50,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/N7TSJFNJM3KH5STMCZFL2RUSGF","json":"https://pith.science/pith/N7TSJFNJM3KH5STMCZFL2RUSGF.json","graph_json":"https://pith.science/api/pith-number/N7TSJFNJM3KH5STMCZFL2RUSGF/graph.json","events_json":"https://pith.science/api/pith-number/N7TSJFNJM3KH5STMCZFL2RUSGF/events.json","paper":"https://pith.science/paper/N7TSJFNJ"},"agent_actions":{"view_html":"https://pith.science/pith/N7TSJFNJM3KH5STMCZFL2RUSGF","download_json":"https://pith.science/pith/N7TSJFNJM3KH5STMCZFL2RUSGF.json","view_paper":"https://pith.science/paper/N7TSJFNJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.03142&json=true","fetch_graph":"https://pith.science/api/pith-number/N7TSJFNJM3KH5STMCZFL2RUSGF/graph.json","fetch_events":"https://pith.science/api/pith-number/N7TSJFNJM3KH5STMCZFL2RUSGF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/N7TSJFNJM3KH5STMCZFL2RUSGF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/N7TSJFNJM3KH5STMCZFL2RUSGF/action/storage_attestation","attest_author":"https://pith.science/pith/N7TSJFNJM3KH5STMCZFL2RUSGF/action/author_attestation","sign_citation":"https://pith.science/pith/N7TSJFNJM3KH5STMCZFL2RUSGF/action/citation_signature","submit_replication":"https://pith.science/pith/N7TSJFNJM3KH5STMCZFL2RUSGF/action/replication_record"}},"created_at":"2026-05-18T01:15:07.448621+00:00","updated_at":"2026-05-18T01:15:07.448621+00:00"}