{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:LXN2OL7WO5CP3W4IMKLA4SN545","short_pith_number":"pith:LXN2OL7W","canonical_record":{"source":{"id":"1709.04553","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-13T22:05:01Z","cross_cats_sorted":[],"title_canon_sha256":"da80465acb340093a33b8dd4c9a7f139a90dac50f665b72fb2bd3b6cce497f28","abstract_canon_sha256":"a7c7b18002fa3713d9649d16318a4893d15b5ed620d747334e7325915640336e"},"schema_version":"1.0"},"canonical_sha256":"5ddba72ff67744fddb8862960e49bde76c4633457f6f1c6b14f9ffdefa36af22","source":{"kind":"arxiv","id":"1709.04553","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.04553","created_at":"2026-05-18T00:35:11Z"},{"alias_kind":"arxiv_version","alias_value":"1709.04553v1","created_at":"2026-05-18T00:35:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.04553","created_at":"2026-05-18T00:35:11Z"},{"alias_kind":"pith_short_12","alias_value":"LXN2OL7WO5CP","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LXN2OL7WO5CP3W4I","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LXN2OL7W","created_at":"2026-05-18T12:31:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:LXN2OL7WO5CP3W4IMKLA4SN545","target":"record","payload":{"canonical_record":{"source":{"id":"1709.04553","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-13T22:05:01Z","cross_cats_sorted":[],"title_canon_sha256":"da80465acb340093a33b8dd4c9a7f139a90dac50f665b72fb2bd3b6cce497f28","abstract_canon_sha256":"a7c7b18002fa3713d9649d16318a4893d15b5ed620d747334e7325915640336e"},"schema_version":"1.0"},"canonical_sha256":"5ddba72ff67744fddb8862960e49bde76c4633457f6f1c6b14f9ffdefa36af22","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:35:11.299430Z","signature_b64":"ENknVDggX5TC59fr4K0u6RJBN2GVazXBAI5MAp/qIwm9Ze41c0PH8tea8SeDioukgKlt0q05Y6xGuN3yeA9+BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5ddba72ff67744fddb8862960e49bde76c4633457f6f1c6b14f9ffdefa36af22","last_reissued_at":"2026-05-18T00:35:11.298870Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:35:11.298870Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.04553","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":"2026-05-18T00:35:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NYwQ+F16h6zx5vIQz0Jc6FgqEB7mjMAVyi0mpTuX9JJY6/QoA9567zwuLc5Xc2rgp/hiL9ntJ5UetqGHNkA4AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T10:26:44.200768Z"},"content_sha256":"0145e7e2089bcfdc470fa807dcbcb8c3c71f9f8b51aad434c86711ea8c1964cf","schema_version":"1.0","event_id":"sha256:0145e7e2089bcfdc470fa807dcbcb8c3c71f9f8b51aad434c86711ea8c1964cf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:LXN2OL7WO5CP3W4IMKLA4SN545","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MOLTE: a Modular Optimal Learning Testing Environment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Warren Powell, Yingfei Wang","submitted_at":"2017-09-13T22:05:01Z","abstract_excerpt":"We address the relative paucity of empirical testing of learning algorithms (of any type) by introducing a new public-domain, Modular, Optimal Learning Testing Environment (MOLTE) for Bayesian ranking and selection problem, stochastic bandits or sequential experimental design problems. The Matlab-based simulator allows the comparison of a number of learning policies (represented as a series of .m modules) in the context of a wide range of problems (each represented in its own .m module) which makes it easy to add new algorithms and new test problems. State-of-the-art policies and various probl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.04553","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":"2026-05-18T00:35:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DHkNCpa2HX7DNIBSxXzsPh2kvKjNs1CzNwC9lxQ7IWUmno/8cOlI0ilUkZNqfFboFhlCakpLsFH222dOT5zhAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T10:26:44.201113Z"},"content_sha256":"d52c743157ff7f8367126895b20c20f1671faaa8bb6d6ca0c26f47005a9babcf","schema_version":"1.0","event_id":"sha256:d52c743157ff7f8367126895b20c20f1671faaa8bb6d6ca0c26f47005a9babcf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LXN2OL7WO5CP3W4IMKLA4SN545/bundle.json","state_url":"https://pith.science/pith/LXN2OL7WO5CP3W4IMKLA4SN545/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LXN2OL7WO5CP3W4IMKLA4SN545/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":"2026-06-04T10:26:44Z","links":{"resolver":"https://pith.science/pith/LXN2OL7WO5CP3W4IMKLA4SN545","bundle":"https://pith.science/pith/LXN2OL7WO5CP3W4IMKLA4SN545/bundle.json","state":"https://pith.science/pith/LXN2OL7WO5CP3W4IMKLA4SN545/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LXN2OL7WO5CP3W4IMKLA4SN545/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LXN2OL7WO5CP3W4IMKLA4SN545","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":"a7c7b18002fa3713d9649d16318a4893d15b5ed620d747334e7325915640336e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-13T22:05:01Z","title_canon_sha256":"da80465acb340093a33b8dd4c9a7f139a90dac50f665b72fb2bd3b6cce497f28"},"schema_version":"1.0","source":{"id":"1709.04553","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.04553","created_at":"2026-05-18T00:35:11Z"},{"alias_kind":"arxiv_version","alias_value":"1709.04553v1","created_at":"2026-05-18T00:35:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.04553","created_at":"2026-05-18T00:35:11Z"},{"alias_kind":"pith_short_12","alias_value":"LXN2OL7WO5CP","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LXN2OL7WO5CP3W4I","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LXN2OL7W","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:d52c743157ff7f8367126895b20c20f1671faaa8bb6d6ca0c26f47005a9babcf","target":"graph","created_at":"2026-05-18T00:35:11Z","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":"We address the relative paucity of empirical testing of learning algorithms (of any type) by introducing a new public-domain, Modular, Optimal Learning Testing Environment (MOLTE) for Bayesian ranking and selection problem, stochastic bandits or sequential experimental design problems. The Matlab-based simulator allows the comparison of a number of learning policies (represented as a series of .m modules) in the context of a wide range of problems (each represented in its own .m module) which makes it easy to add new algorithms and new test problems. State-of-the-art policies and various probl","authors_text":"Warren Powell, Yingfei Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-13T22:05:01Z","title":"MOLTE: a Modular Optimal Learning Testing Environment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.04553","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":"sha256:0145e7e2089bcfdc470fa807dcbcb8c3c71f9f8b51aad434c86711ea8c1964cf","target":"record","created_at":"2026-05-18T00:35:11Z","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":"a7c7b18002fa3713d9649d16318a4893d15b5ed620d747334e7325915640336e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-13T22:05:01Z","title_canon_sha256":"da80465acb340093a33b8dd4c9a7f139a90dac50f665b72fb2bd3b6cce497f28"},"schema_version":"1.0","source":{"id":"1709.04553","kind":"arxiv","version":1}},"canonical_sha256":"5ddba72ff67744fddb8862960e49bde76c4633457f6f1c6b14f9ffdefa36af22","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5ddba72ff67744fddb8862960e49bde76c4633457f6f1c6b14f9ffdefa36af22","first_computed_at":"2026-05-18T00:35:11.298870Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:35:11.298870Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ENknVDggX5TC59fr4K0u6RJBN2GVazXBAI5MAp/qIwm9Ze41c0PH8tea8SeDioukgKlt0q05Y6xGuN3yeA9+BA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:35:11.299430Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.04553","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0145e7e2089bcfdc470fa807dcbcb8c3c71f9f8b51aad434c86711ea8c1964cf","sha256:d52c743157ff7f8367126895b20c20f1671faaa8bb6d6ca0c26f47005a9babcf"],"state_sha256":"d65b6bf2a5922e5a1ad41a662aabaf22cd90c548e18541397d3be9df3174f063"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WbNk36/h16nG3q1yYXFqNusse8VIN4wMfRZVkxjo0vxpXO4WdOPNB9uq4MSEP96InRwEoqj5i4jTZKJWfdfkAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T10:26:44.203126Z","bundle_sha256":"24dae82d154a4872c7ec402b0999b1c6ab88275c57bc620c4bdda646881f33e4"}}