{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:QB464C5HBNU2AAIGN63R2ORGMV","short_pith_number":"pith:QB464C5H","canonical_record":{"source":{"id":"1910.00211","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-10-01T06:16:48Z","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"title_canon_sha256":"32e3e17950f5e961b7ecc75fa02eff1737522062e4b416f9294f06571360c5d6","abstract_canon_sha256":"bdf837088592e1d32ea7f2ea724fc9e329a07515f5b89cca7afe79709df299d7"},"schema_version":"1.0"},"canonical_sha256":"8079ee0ba70b69a001066fb71d3a26656625104e3f7f2cfbc545efdc4e7e63f4","source":{"kind":"arxiv","id":"1910.00211","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.00211","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"arxiv_version","alias_value":"1910.00211v1","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.00211","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"pith_short_12","alias_value":"QB464C5HBNU2","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"pith_short_16","alias_value":"QB464C5HBNU2AAIG","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"pith_short_8","alias_value":"QB464C5H","created_at":"2026-07-05T00:08:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:QB464C5HBNU2AAIGN63R2ORGMV","target":"record","payload":{"canonical_record":{"source":{"id":"1910.00211","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-10-01T06:16:48Z","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"title_canon_sha256":"32e3e17950f5e961b7ecc75fa02eff1737522062e4b416f9294f06571360c5d6","abstract_canon_sha256":"bdf837088592e1d32ea7f2ea724fc9e329a07515f5b89cca7afe79709df299d7"},"schema_version":"1.0"},"canonical_sha256":"8079ee0ba70b69a001066fb71d3a26656625104e3f7f2cfbc545efdc4e7e63f4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:08:43.758635Z","signature_b64":"s5Jej3hCP2ZEOxFxDXfXvWD2adHyvgNtwqwp9v2o7UzK9FuocH4z45KyOazaDmif6ON8yEjnqOIyRTKWBU/PBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8079ee0ba70b69a001066fb71d3a26656625104e3f7f2cfbc545efdc4e7e63f4","last_reissued_at":"2026-07-05T00:08:43.758245Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:08:43.758245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1910.00211","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":"2026-07-05T00:08:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VN/ixeMTn+ONR4IL41ecO6yGt+ionehy8a2X5SMEe7oC5wb9VQYO6yMJkJqeVjHgq36k8w38wbMO5dkE/kl8Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T19:26:08.553111Z"},"content_sha256":"68a486900959dd5971ad17d0b85b0dd13a7ca52760da6b5c91f8f1aca7168390","schema_version":"1.0","event_id":"sha256:68a486900959dd5971ad17d0b85b0dd13a7ca52760da6b5c91f8f1aca7168390"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:QB464C5HBNU2AAIGN63R2ORGMV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SY","eess.SY"],"primary_cat":"cs.AI","authors_text":"Balaraman Ravindran, Hardik Meisheri, Harshad Khadilkar, Nazneen N Sultana, Vinita Baniwal","submitted_at":"2019-10-01T06:16:48Z","abstract_excerpt":"This paper describes a purely data-driven solution to a class of sequential decision-making problems with a large number of concurrent online decisions, with applications to computing systems and operations research. We assume that while the micro-level behaviour of the system can be broadly captured by analytical expressions or simulation, the macro-level or emergent behaviour is complicated by non-linearity, constraints, and stochasticity. If we represent the set of concurrent decisions to be computed as a vector, each element of the vector is assumed to be a continuous variable, and the num"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.00211","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/1910.00211/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":"2026-07-05T00:08:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XXuw4440I3rJ2rPM9/574soHVX1IJHcZ0Ct4JM0sIRMtG+coRnHnEpkCNzrzVkpZnGqXJuAW0chZec1cKOlXDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T19:26:08.553743Z"},"content_sha256":"9b87002f5c3406210708dda97d5cb435188190e3e6160b7799150c58da2aec31","schema_version":"1.0","event_id":"sha256:9b87002f5c3406210708dda97d5cb435188190e3e6160b7799150c58da2aec31"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QB464C5HBNU2AAIGN63R2ORGMV/bundle.json","state_url":"https://pith.science/pith/QB464C5HBNU2AAIGN63R2ORGMV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QB464C5HBNU2AAIGN63R2ORGMV/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":"2026-08-11T19:26:08Z","links":{"resolver":"https://pith.science/pith/QB464C5HBNU2AAIGN63R2ORGMV","bundle":"https://pith.science/pith/QB464C5HBNU2AAIGN63R2ORGMV/bundle.json","state":"https://pith.science/pith/QB464C5HBNU2AAIGN63R2ORGMV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QB464C5HBNU2AAIGN63R2ORGMV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:QB464C5HBNU2AAIGN63R2ORGMV","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":"bdf837088592e1d32ea7f2ea724fc9e329a07515f5b89cca7afe79709df299d7","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-10-01T06:16:48Z","title_canon_sha256":"32e3e17950f5e961b7ecc75fa02eff1737522062e4b416f9294f06571360c5d6"},"schema_version":"1.0","source":{"id":"1910.00211","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.00211","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"arxiv_version","alias_value":"1910.00211v1","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.00211","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"pith_short_12","alias_value":"QB464C5HBNU2","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"pith_short_16","alias_value":"QB464C5HBNU2AAIG","created_at":"2026-07-05T00:08:43Z"},{"alias_kind":"pith_short_8","alias_value":"QB464C5H","created_at":"2026-07-05T00:08:43Z"}],"graph_snapshots":[{"event_id":"sha256:9b87002f5c3406210708dda97d5cb435188190e3e6160b7799150c58da2aec31","target":"graph","created_at":"2026-07-05T00:08:43Z","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/1910.00211/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper describes a purely data-driven solution to a class of sequential decision-making problems with a large number of concurrent online decisions, with applications to computing systems and operations research. We assume that while the micro-level behaviour of the system can be broadly captured by analytical expressions or simulation, the macro-level or emergent behaviour is complicated by non-linearity, constraints, and stochasticity. If we represent the set of concurrent decisions to be computed as a vector, each element of the vector is assumed to be a continuous variable, and the num","authors_text":"Balaraman Ravindran, Hardik Meisheri, Harshad Khadilkar, Nazneen N Sultana, Vinita Baniwal","cross_cats":["cs.LG","cs.SY","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-10-01T06:16:48Z","title":"Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.00211","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":"sha256:68a486900959dd5971ad17d0b85b0dd13a7ca52760da6b5c91f8f1aca7168390","target":"record","created_at":"2026-07-05T00:08:43Z","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":"bdf837088592e1d32ea7f2ea724fc9e329a07515f5b89cca7afe79709df299d7","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-10-01T06:16:48Z","title_canon_sha256":"32e3e17950f5e961b7ecc75fa02eff1737522062e4b416f9294f06571360c5d6"},"schema_version":"1.0","source":{"id":"1910.00211","kind":"arxiv","version":1}},"canonical_sha256":"8079ee0ba70b69a001066fb71d3a26656625104e3f7f2cfbc545efdc4e7e63f4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8079ee0ba70b69a001066fb71d3a26656625104e3f7f2cfbc545efdc4e7e63f4","first_computed_at":"2026-07-05T00:08:43.758245Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:08:43.758245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s5Jej3hCP2ZEOxFxDXfXvWD2adHyvgNtwqwp9v2o7UzK9FuocH4z45KyOazaDmif6ON8yEjnqOIyRTKWBU/PBw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:08:43.758635Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.00211","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68a486900959dd5971ad17d0b85b0dd13a7ca52760da6b5c91f8f1aca7168390","sha256:9b87002f5c3406210708dda97d5cb435188190e3e6160b7799150c58da2aec31"],"state_sha256":"24d447f4c00e3d83205ca50c04618bf344e0e09cb549a87680473f76c500a305"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Wa79+BunwiQ9b8p4aFdt+BX0EWWbkMRpOSAUfbMCQr70YG5sG0e5pt/PF19Jsf7DZmADnUN6hTrCBz/GwTDLDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T19:26:08.570968Z","bundle_sha256":"d20d16046de0eee7fce9fd6185e4f74a653b8bf4630073e74169ce2ca3d924e2"}}