{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:ETXZIAHEJMAY3L4LDWFAQVKSK3","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":"6128061272288779e2712a3958b52cfd903557320da592ff57d745d31e1e438e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-02T13:32:21Z","title_canon_sha256":"35228e3ea8453c45c0ac4cc456d08acba66f47bb81438e9e814e7a492b1346a9"},"schema_version":"1.0","source":{"id":"2111.01587","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.01587","created_at":"2026-07-05T03:28:30Z"},{"alias_kind":"arxiv_version","alias_value":"2111.01587v1","created_at":"2026-07-05T03:28:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.01587","created_at":"2026-07-05T03:28:30Z"},{"alias_kind":"pith_short_12","alias_value":"ETXZIAHEJMAY","created_at":"2026-07-05T03:28:30Z"},{"alias_kind":"pith_short_16","alias_value":"ETXZIAHEJMAY3L4L","created_at":"2026-07-05T03:28:30Z"},{"alias_kind":"pith_short_8","alias_value":"ETXZIAHE","created_at":"2026-07-05T03:28:30Z"}],"graph_snapshots":[{"event_id":"sha256:f8c256f6dca739d0d8feac0d715cc16959b4fbdb29987d56d426a81262a6095b","target":"graph","created_at":"2026-07-05T03:28:30Z","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/2111.01587/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"One of the key promises of model-based reinforcement learning is the ability to generalize using an internal model of the world to make predictions in novel environments and tasks. However, the generalization ability of model-based agents is not well understood because existing work has focused on model-free agents when benchmarking generalization. Here, we explicitly measure the generalization ability of model-based agents in comparison to their model-free counterparts. We focus our analysis on MuZero (Schrittwieser et al., 2020), a powerful model-based agent, and evaluate its performance on ","authors_text":"Ankesh Anand, Eszter V\\'ertes, Jacob Walker, Jessica B. Hamrick, Julian Schrittwieser, Sherjil Ozair, Th\\'eophane Weber, Yazhe Li","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-02T13:32:21Z","title":"Procedural Generalization by Planning with Self-Supervised World Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.01587","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:f7add7048f97e8ed1955dad8c1b4ad228b8489221bf49adf4db673decbce6140","target":"record","created_at":"2026-07-05T03:28:30Z","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":"6128061272288779e2712a3958b52cfd903557320da592ff57d745d31e1e438e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-02T13:32:21Z","title_canon_sha256":"35228e3ea8453c45c0ac4cc456d08acba66f47bb81438e9e814e7a492b1346a9"},"schema_version":"1.0","source":{"id":"2111.01587","kind":"arxiv","version":1}},"canonical_sha256":"24ef9400e44b018daf8b1d8a08555256caa41137f8624d96dca0c6503ab3943f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"24ef9400e44b018daf8b1d8a08555256caa41137f8624d96dca0c6503ab3943f","first_computed_at":"2026-07-05T03:28:30.531471Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:28:30.531471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5ZcmZMi+1/WjUg4L5RtABgfHE/SbPCTeog4l0W+aKcE1AjcaUUzx1EK15DE68qINqvw72k1L7YFGF7VMd3LvCw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:28:30.531946Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.01587","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f7add7048f97e8ed1955dad8c1b4ad228b8489221bf49adf4db673decbce6140","sha256:f8c256f6dca739d0d8feac0d715cc16959b4fbdb29987d56d426a81262a6095b"],"state_sha256":"232b665941c717e7b8ebdda76d93c098dd215493e1bb38a2be153867111759e1"}