{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:M5VRE6N473BL657VGYZT354UG3","short_pith_number":"pith:M5VRE6N4","canonical_record":{"source":{"id":"1401.8074","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2014-01-31T07:02:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7c606f12353379f2fa469d57a66156979479b25fbc39954669c247caf5d29e27","abstract_canon_sha256":"72b52244a031208a59a6477f91b07ce7671ada56c7021c107feca32b69f4bb88"},"schema_version":"1.0"},"canonical_sha256":"676b1279bcfec2bf77f536333df79436e19dc9b1d7431df7f2ea448a53330232","source":{"kind":"arxiv","id":"1401.8074","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1401.8074","created_at":"2026-05-18T03:00:36Z"},{"alias_kind":"arxiv_version","alias_value":"1401.8074v1","created_at":"2026-05-18T03:00:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1401.8074","created_at":"2026-05-18T03:00:36Z"},{"alias_kind":"pith_short_12","alias_value":"M5VRE6N473BL","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_16","alias_value":"M5VRE6N473BL657V","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_8","alias_value":"M5VRE6N4","created_at":"2026-05-18T12:28:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:M5VRE6N473BL657VGYZT354UG3","target":"record","payload":{"canonical_record":{"source":{"id":"1401.8074","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2014-01-31T07:02:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7c606f12353379f2fa469d57a66156979479b25fbc39954669c247caf5d29e27","abstract_canon_sha256":"72b52244a031208a59a6477f91b07ce7671ada56c7021c107feca32b69f4bb88"},"schema_version":"1.0"},"canonical_sha256":"676b1279bcfec2bf77f536333df79436e19dc9b1d7431df7f2ea448a53330232","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:00:36.236564Z","signature_b64":"vjXbnbIYhjch/3nyZmyB0vzzpHtYmUEwg0e+dDpdyveDwpVtbOowUWVSyK4g3gReY861MRNtO9j8mRdUQeCqAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"676b1279bcfec2bf77f536333df79436e19dc9b1d7431df7f2ea448a53330232","last_reissued_at":"2026-05-18T03:00:36.235655Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:00:36.235655Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1401.8074","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":"2026-05-18T03:00:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nnfgsk1tt0OKJ4iOpc7Wml1KMKiu1YnOJkHotzD2DcOaHY/CGHSiwMUuPQFpKFnhaCk1MsK4hoUHdAZFMAoxBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T22:00:54.107828Z"},"content_sha256":"ed6d556d5a72e6685b7b00e53f9d1fb07c497e2c16e236775517d8f4c8200506","schema_version":"1.0","event_id":"sha256:ed6d556d5a72e6685b7b00e53f9d1fb07c497e2c16e236775517d8f4c8200506"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:M5VRE6N473BL657VGYZT354UG3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Empirically Evaluating Multiagent Learning Algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.GT","authors_text":"Asher Lipson, Erik Zawadzki, Kevin Leyton-Brown","submitted_at":"2014-01-31T07:02:58Z","abstract_excerpt":"There exist many algorithms for learning how to play repeated bimatrix games. Most of these algorithms are justified in terms of some sort of theoretical guarantee. On the other hand, little is known about the empirical performance of these algorithms. Most such claims in the literature are based on small experiments, which has hampered understanding as well as the development of new multiagent learning (MAL) algorithms. We have developed a new suite of tools for running multiagent experiments: the MultiAgent Learning Testbed (MALT). These tools are designed to facilitate larger and more compr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1401.8074","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:00:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8MMq030ANU3wK3RhJ6cbJclUJYUozMZSQ4roAL6aXCwfBGuRwmDopV6iRo8VCuHwClECzMe4v3fwYsezH2K2Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T22:00:54.108277Z"},"content_sha256":"7876ba52297d038490a151d17a17981284672ce0c02170b7281cbdc9c35ff871","schema_version":"1.0","event_id":"sha256:7876ba52297d038490a151d17a17981284672ce0c02170b7281cbdc9c35ff871"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M5VRE6N473BL657VGYZT354UG3/bundle.json","state_url":"https://pith.science/pith/M5VRE6N473BL657VGYZT354UG3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M5VRE6N473BL657VGYZT354UG3/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":"2026-08-23T22:00:54Z","links":{"resolver":"https://pith.science/pith/M5VRE6N473BL657VGYZT354UG3","bundle":"https://pith.science/pith/M5VRE6N473BL657VGYZT354UG3/bundle.json","state":"https://pith.science/pith/M5VRE6N473BL657VGYZT354UG3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M5VRE6N473BL657VGYZT354UG3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:M5VRE6N473BL657VGYZT354UG3","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":"72b52244a031208a59a6477f91b07ce7671ada56c7021c107feca32b69f4bb88","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2014-01-31T07:02:58Z","title_canon_sha256":"7c606f12353379f2fa469d57a66156979479b25fbc39954669c247caf5d29e27"},"schema_version":"1.0","source":{"id":"1401.8074","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1401.8074","created_at":"2026-05-18T03:00:36Z"},{"alias_kind":"arxiv_version","alias_value":"1401.8074v1","created_at":"2026-05-18T03:00:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1401.8074","created_at":"2026-05-18T03:00:36Z"},{"alias_kind":"pith_short_12","alias_value":"M5VRE6N473BL","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_16","alias_value":"M5VRE6N473BL657V","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_8","alias_value":"M5VRE6N4","created_at":"2026-05-18T12:28:38Z"}],"graph_snapshots":[{"event_id":"sha256:7876ba52297d038490a151d17a17981284672ce0c02170b7281cbdc9c35ff871","target":"graph","created_at":"2026-05-18T03:00:36Z","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"},"paper":{"abstract_excerpt":"There exist many algorithms for learning how to play repeated bimatrix games. Most of these algorithms are justified in terms of some sort of theoretical guarantee. On the other hand, little is known about the empirical performance of these algorithms. Most such claims in the literature are based on small experiments, which has hampered understanding as well as the development of new multiagent learning (MAL) algorithms. We have developed a new suite of tools for running multiagent experiments: the MultiAgent Learning Testbed (MALT). These tools are designed to facilitate larger and more compr","authors_text":"Asher Lipson, Erik Zawadzki, Kevin Leyton-Brown","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2014-01-31T07:02:58Z","title":"Empirically Evaluating Multiagent Learning Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1401.8074","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:ed6d556d5a72e6685b7b00e53f9d1fb07c497e2c16e236775517d8f4c8200506","target":"record","created_at":"2026-05-18T03:00:36Z","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":"72b52244a031208a59a6477f91b07ce7671ada56c7021c107feca32b69f4bb88","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2014-01-31T07:02:58Z","title_canon_sha256":"7c606f12353379f2fa469d57a66156979479b25fbc39954669c247caf5d29e27"},"schema_version":"1.0","source":{"id":"1401.8074","kind":"arxiv","version":1}},"canonical_sha256":"676b1279bcfec2bf77f536333df79436e19dc9b1d7431df7f2ea448a53330232","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"676b1279bcfec2bf77f536333df79436e19dc9b1d7431df7f2ea448a53330232","first_computed_at":"2026-05-18T03:00:36.235655Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:00:36.235655Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vjXbnbIYhjch/3nyZmyB0vzzpHtYmUEwg0e+dDpdyveDwpVtbOowUWVSyK4g3gReY861MRNtO9j8mRdUQeCqAg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:00:36.236564Z","signed_message":"canonical_sha256_bytes"},"source_id":"1401.8074","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ed6d556d5a72e6685b7b00e53f9d1fb07c497e2c16e236775517d8f4c8200506","sha256:7876ba52297d038490a151d17a17981284672ce0c02170b7281cbdc9c35ff871"],"state_sha256":"b8999cbb857f002fd1e7d13e617c4c025c97e3fc0d93bb90ba1cd7a29a733081"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JQ0Zf2KudpZYQHL6Qh6bkANfGuZx3KgGjLVW5PuHU/o+6ljnawY1d26nj/XIjrI60PYoGRDfQuOdogv/UC5qCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T22:00:54.112701Z","bundle_sha256":"ccf4de97cde952e19898fd2d85082d2caa7931bd1b0373098da3627e247bc449"}}