{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:N5VID7V6FK67TO7V4A7XGLEATO","short_pith_number":"pith:N5VID7V6","canonical_record":{"source":{"id":"2310.08348","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-12T14:18:09Z","cross_cats_sorted":[],"title_canon_sha256":"e22d1fdafd130c598a0027067cb652e06dbcad6515f0c623641369d73f8b89df","abstract_canon_sha256":"85b09f2294a8b3e2e1427ebab94ba5445a6c8f02fc01783c6471d8ae06d3d26f"},"schema_version":"1.0"},"canonical_sha256":"6f6a81febe2abdf9bbf5e03f732c809ba2974e267610fd16481bb22a12695040","source":{"kind":"arxiv","id":"2310.08348","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.08348","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"arxiv_version","alias_value":"2310.08348v1","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.08348","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"pith_short_12","alias_value":"N5VID7V6FK67","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"pith_short_16","alias_value":"N5VID7V6FK67TO7V","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"pith_short_8","alias_value":"N5VID7V6","created_at":"2026-07-05T07:00:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:N5VID7V6FK67TO7V4A7XGLEATO","target":"record","payload":{"canonical_record":{"source":{"id":"2310.08348","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-12T14:18:09Z","cross_cats_sorted":[],"title_canon_sha256":"e22d1fdafd130c598a0027067cb652e06dbcad6515f0c623641369d73f8b89df","abstract_canon_sha256":"85b09f2294a8b3e2e1427ebab94ba5445a6c8f02fc01783c6471d8ae06d3d26f"},"schema_version":"1.0"},"canonical_sha256":"6f6a81febe2abdf9bbf5e03f732c809ba2974e267610fd16481bb22a12695040","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:00:14.335918Z","signature_b64":"hS4fFILDikC4ebYOT9KK8v8OGpCI7TkdJVwF+Lmkur/M+j40+fmemUlGFUd2VmqGe5jOGopxHJfVYUK1LpRHAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6f6a81febe2abdf9bbf5e03f732c809ba2974e267610fd16481bb22a12695040","last_reissued_at":"2026-07-05T07:00:14.335390Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:00:14.335390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.08348","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":"2026-07-05T07:00:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XsEaDOQWaVFdCFcT60VEw2x21eOd+EapV+GXP7uEGwSajf7Pqw0lzonslQ/5kXb1C/wTCwJnwq1iwskYgXhKAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T22:08:19.155856Z"},"content_sha256":"e7e421cf4f169208aab6b0a8876a2665a71196011472408a1b06a4fd1a3a26c7","schema_version":"1.0","event_id":"sha256:e7e421cf4f169208aab6b0a8876a2665a71196011472408a1b06a4fd1a3a26c7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:N5VID7V6FK67TO7V4A7XGLEATO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Hongsheng Li, Jiyuan Ren, Shuai Hu, Tong Zhou, Xueyan Li, Yazhe Niu, Yuan Pu, Yu Liu, Zhenjie Yang","submitted_at":"2023-10-12T14:18:09Z","abstract_excerpt":"Building agents based on tree-search planning capabilities with learned models has achieved remarkable success in classic decision-making problems, such as Go and Atari. However, it has been deemed challenging or even infeasible to extend Monte Carlo Tree Search (MCTS) based algorithms to diverse real-world applications, especially when these environments involve complex action spaces and significant simulation costs, or inherent stochasticity. In this work, we introduce LightZero, the first unified benchmark for deploying MCTS/MuZero in general sequential decision scenarios. Specificially, we"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.08348","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/2310.08348/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":"2026-07-05T07:00:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vz9Tk9qEedFJsa/KcyKc+6XfO23ptF4RS+ESyuQ46ub7M9os0G148W20xBm6hqPF0xwah8A9JZAYcPeqLsmDAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T22:08:19.156559Z"},"content_sha256":"e9969469a226ffef5ed2afca3a8faf447ba730f2da039705c0806493682b54db","schema_version":"1.0","event_id":"sha256:e9969469a226ffef5ed2afca3a8faf447ba730f2da039705c0806493682b54db"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N5VID7V6FK67TO7V4A7XGLEATO/bundle.json","state_url":"https://pith.science/pith/N5VID7V6FK67TO7V4A7XGLEATO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N5VID7V6FK67TO7V4A7XGLEATO/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":"2026-08-04T22:08:19Z","links":{"resolver":"https://pith.science/pith/N5VID7V6FK67TO7V4A7XGLEATO","bundle":"https://pith.science/pith/N5VID7V6FK67TO7V4A7XGLEATO/bundle.json","state":"https://pith.science/pith/N5VID7V6FK67TO7V4A7XGLEATO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N5VID7V6FK67TO7V4A7XGLEATO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:N5VID7V6FK67TO7V4A7XGLEATO","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":"85b09f2294a8b3e2e1427ebab94ba5445a6c8f02fc01783c6471d8ae06d3d26f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-12T14:18:09Z","title_canon_sha256":"e22d1fdafd130c598a0027067cb652e06dbcad6515f0c623641369d73f8b89df"},"schema_version":"1.0","source":{"id":"2310.08348","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.08348","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"arxiv_version","alias_value":"2310.08348v1","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.08348","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"pith_short_12","alias_value":"N5VID7V6FK67","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"pith_short_16","alias_value":"N5VID7V6FK67TO7V","created_at":"2026-07-05T07:00:14Z"},{"alias_kind":"pith_short_8","alias_value":"N5VID7V6","created_at":"2026-07-05T07:00:14Z"}],"graph_snapshots":[{"event_id":"sha256:e9969469a226ffef5ed2afca3a8faf447ba730f2da039705c0806493682b54db","target":"graph","created_at":"2026-07-05T07:00:14Z","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/2310.08348/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Building agents based on tree-search planning capabilities with learned models has achieved remarkable success in classic decision-making problems, such as Go and Atari. However, it has been deemed challenging or even infeasible to extend Monte Carlo Tree Search (MCTS) based algorithms to diverse real-world applications, especially when these environments involve complex action spaces and significant simulation costs, or inherent stochasticity. In this work, we introduce LightZero, the first unified benchmark for deploying MCTS/MuZero in general sequential decision scenarios. Specificially, we","authors_text":"Hongsheng Li, Jiyuan Ren, Shuai Hu, Tong Zhou, Xueyan Li, Yazhe Niu, Yuan Pu, Yu Liu, Zhenjie Yang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-12T14:18:09Z","title":"LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.08348","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:e7e421cf4f169208aab6b0a8876a2665a71196011472408a1b06a4fd1a3a26c7","target":"record","created_at":"2026-07-05T07:00:14Z","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":"85b09f2294a8b3e2e1427ebab94ba5445a6c8f02fc01783c6471d8ae06d3d26f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-12T14:18:09Z","title_canon_sha256":"e22d1fdafd130c598a0027067cb652e06dbcad6515f0c623641369d73f8b89df"},"schema_version":"1.0","source":{"id":"2310.08348","kind":"arxiv","version":1}},"canonical_sha256":"6f6a81febe2abdf9bbf5e03f732c809ba2974e267610fd16481bb22a12695040","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6f6a81febe2abdf9bbf5e03f732c809ba2974e267610fd16481bb22a12695040","first_computed_at":"2026-07-05T07:00:14.335390Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:00:14.335390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hS4fFILDikC4ebYOT9KK8v8OGpCI7TkdJVwF+Lmkur/M+j40+fmemUlGFUd2VmqGe5jOGopxHJfVYUK1LpRHAA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:00:14.335918Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.08348","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e7e421cf4f169208aab6b0a8876a2665a71196011472408a1b06a4fd1a3a26c7","sha256:e9969469a226ffef5ed2afca3a8faf447ba730f2da039705c0806493682b54db"],"state_sha256":"2f53e5851caeca70fedf778e087c8de563c2518dbfb008e978c25d547f7f92d5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WVUcnXTvmR27ZE/BqGxxfWUVfJ/6RJhrKjztaE1d6LxsOcMx13d5cNZzH7mZZz8Swgrv7uf59tqEWJsdexAqDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T22:08:19.161663Z","bundle_sha256":"fae0230401c95b2009cec9aaf2d4f60d50df3c5abd613bf0f8ae600c7cfc801c"}}