{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:AVXMO4ZJYDAT55DKP2CVGLV5EU","short_pith_number":"pith:AVXMO4ZJ","canonical_record":{"source":{"id":"1611.07420","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2016-11-10T15:48:08Z","cross_cats_sorted":[],"title_canon_sha256":"8c08492a8eb6e7df4bdeace3b929c8e48fdb402f1b19ecfc11645f7b08eaaa08","abstract_canon_sha256":"e8c4507877eadfb8b75e761b6d13a973b0a6239ef8b13817e03713a6fd6e3325"},"schema_version":"1.0"},"canonical_sha256":"056ec77329c0c13ef46a7e85532ebd25096ad76bbb08bede9cc084c5822266a3","source":{"kind":"arxiv","id":"1611.07420","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.07420","created_at":"2026-05-18T00:57:20Z"},{"alias_kind":"arxiv_version","alias_value":"1611.07420v1","created_at":"2026-05-18T00:57:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.07420","created_at":"2026-05-18T00:57:20Z"},{"alias_kind":"pith_short_12","alias_value":"AVXMO4ZJYDAT","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AVXMO4ZJYDAT55DK","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AVXMO4ZJ","created_at":"2026-05-18T12:30:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:AVXMO4ZJYDAT55DKP2CVGLV5EU","target":"record","payload":{"canonical_record":{"source":{"id":"1611.07420","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2016-11-10T15:48:08Z","cross_cats_sorted":[],"title_canon_sha256":"8c08492a8eb6e7df4bdeace3b929c8e48fdb402f1b19ecfc11645f7b08eaaa08","abstract_canon_sha256":"e8c4507877eadfb8b75e761b6d13a973b0a6239ef8b13817e03713a6fd6e3325"},"schema_version":"1.0"},"canonical_sha256":"056ec77329c0c13ef46a7e85532ebd25096ad76bbb08bede9cc084c5822266a3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:57:20.166861Z","signature_b64":"mDKQBOv6cDrYNqtcxBliXmTyjQ9dxuo2OHALIjAE1MHdinLSSFJ88k6D1ATwVqMjzFj+F/sqlwmlXHpLpmpCDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"056ec77329c0c13ef46a7e85532ebd25096ad76bbb08bede9cc084c5822266a3","last_reissued_at":"2026-05-18T00:57:20.166259Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:57:20.166259Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1611.07420","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":"2026-05-18T00:57:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zko6SxKT/qbLsqVmUZVEYaVbsIiLi2yqZbwcFd34Ki+Vb5DAvZxzJDhJZzSbFOvx5leVcRdb+y+G5g6teL8CAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T11:34:59.185767Z"},"content_sha256":"16e5df3461262314a14dbdc6e6ecf8f2e7c3dd190f03818c0101e00989a90bbc","schema_version":"1.0","event_id":"sha256:16e5df3461262314a14dbdc6e6ecf8f2e7c3dd190f03818c0101e00989a90bbc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:AVXMO4ZJYDAT55DKP2CVGLV5EU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SMCL - Stochastic Model Checker for Learning in Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Hongyang Qu, Michalis Smyrnakis, Sandor M. Veres","submitted_at":"2016-11-10T15:48:08Z","abstract_excerpt":"A stochastic model checker is presented for analysing the performance of game-theoretic learning algorithms. The method enables the comparison of short-term behaviour of learning algorithms intended for practical use. The procedure of comparison is automated and it can be tuned for accuracy and speed. Users can choose from among various learning algorithms to select a suitable one for a given practical problem. The powerful performance of the method is enabled by a novel behaviour-similarity-relation, which compacts large state spaces into small ones. The stochastic model checking tool is test"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.07420","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":"2026-05-18T00:57:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1GOnd612Eo7cp9d98fdqvJeemJS3mz8W1Oo1WQMjqC3StA2/K/TQHo9/L/FZ23xnt2qV6ueQJfjKT9zQX/bBDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T11:34:59.186114Z"},"content_sha256":"251035b6c0a3536bb17e9116386bb7ddbf53c7c69f942b9c419c25e9f0b9c37b","schema_version":"1.0","event_id":"sha256:251035b6c0a3536bb17e9116386bb7ddbf53c7c69f942b9c419c25e9f0b9c37b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AVXMO4ZJYDAT55DKP2CVGLV5EU/bundle.json","state_url":"https://pith.science/pith/AVXMO4ZJYDAT55DKP2CVGLV5EU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AVXMO4ZJYDAT55DKP2CVGLV5EU/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":"2026-06-01T11:34:59Z","links":{"resolver":"https://pith.science/pith/AVXMO4ZJYDAT55DKP2CVGLV5EU","bundle":"https://pith.science/pith/AVXMO4ZJYDAT55DKP2CVGLV5EU/bundle.json","state":"https://pith.science/pith/AVXMO4ZJYDAT55DKP2CVGLV5EU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AVXMO4ZJYDAT55DKP2CVGLV5EU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:AVXMO4ZJYDAT55DKP2CVGLV5EU","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":"e8c4507877eadfb8b75e761b6d13a973b0a6239ef8b13817e03713a6fd6e3325","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2016-11-10T15:48:08Z","title_canon_sha256":"8c08492a8eb6e7df4bdeace3b929c8e48fdb402f1b19ecfc11645f7b08eaaa08"},"schema_version":"1.0","source":{"id":"1611.07420","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.07420","created_at":"2026-05-18T00:57:20Z"},{"alias_kind":"arxiv_version","alias_value":"1611.07420v1","created_at":"2026-05-18T00:57:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.07420","created_at":"2026-05-18T00:57:20Z"},{"alias_kind":"pith_short_12","alias_value":"AVXMO4ZJYDAT","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AVXMO4ZJYDAT55DK","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AVXMO4ZJ","created_at":"2026-05-18T12:30:07Z"}],"graph_snapshots":[{"event_id":"sha256:251035b6c0a3536bb17e9116386bb7ddbf53c7c69f942b9c419c25e9f0b9c37b","target":"graph","created_at":"2026-05-18T00:57:20Z","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":"A stochastic model checker is presented for analysing the performance of game-theoretic learning algorithms. The method enables the comparison of short-term behaviour of learning algorithms intended for practical use. The procedure of comparison is automated and it can be tuned for accuracy and speed. Users can choose from among various learning algorithms to select a suitable one for a given practical problem. The powerful performance of the method is enabled by a novel behaviour-similarity-relation, which compacts large state spaces into small ones. The stochastic model checking tool is test","authors_text":"Hongyang Qu, Michalis Smyrnakis, Sandor M. Veres","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2016-11-10T15:48:08Z","title":"SMCL - Stochastic Model Checker for Learning in Games"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.07420","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":"sha256:16e5df3461262314a14dbdc6e6ecf8f2e7c3dd190f03818c0101e00989a90bbc","target":"record","created_at":"2026-05-18T00:57:20Z","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":"e8c4507877eadfb8b75e761b6d13a973b0a6239ef8b13817e03713a6fd6e3325","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2016-11-10T15:48:08Z","title_canon_sha256":"8c08492a8eb6e7df4bdeace3b929c8e48fdb402f1b19ecfc11645f7b08eaaa08"},"schema_version":"1.0","source":{"id":"1611.07420","kind":"arxiv","version":1}},"canonical_sha256":"056ec77329c0c13ef46a7e85532ebd25096ad76bbb08bede9cc084c5822266a3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"056ec77329c0c13ef46a7e85532ebd25096ad76bbb08bede9cc084c5822266a3","first_computed_at":"2026-05-18T00:57:20.166259Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:57:20.166259Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mDKQBOv6cDrYNqtcxBliXmTyjQ9dxuo2OHALIjAE1MHdinLSSFJ88k6D1ATwVqMjzFj+F/sqlwmlXHpLpmpCDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:57:20.166861Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.07420","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:16e5df3461262314a14dbdc6e6ecf8f2e7c3dd190f03818c0101e00989a90bbc","sha256:251035b6c0a3536bb17e9116386bb7ddbf53c7c69f942b9c419c25e9f0b9c37b"],"state_sha256":"0172d6134c7d5e2a8d97a0f1e7032734877e17f3adead3f525a4bff01870c11a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jW1/nW+arjjmHrNgY/gQO1yYyvFo9IapTCEtGTPxeYj8C8NhLzqfQFh6Z1NavaVXmXUlfAVA3now7aH1JII4Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T11:34:59.188333Z","bundle_sha256":"1ce01d6b65e87ccba803bb01a8bdad742bf9fb6c97060c01c9eeeac442978106"}}