{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:AFY6JOOF2ZU2M4O6JXXTNUMGSD","short_pith_number":"pith:AFY6JOOF","schema_version":"1.0","canonical_sha256":"0171e4b9c5d669a671de4def36d18690d2f3181a24b369bb1836a462cff448c5","source":{"kind":"arxiv","id":"1312.2039","version":1},"attestation_state":"computed","paper":{"title":"Active Classification for POMDPs: a Kalman-like State Estimator","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.SY","authors_text":"Daphney-Stavroula Zois, Marco Levorato, Urbashi Mitra","submitted_at":"2013-12-06T23:57:45Z","abstract_excerpt":"The problem of state tracking with active observation control is considered for a system modeled by a discrete-time, finite-state Markov chain observed through conditionally Gaussian measurement vectors. The measurement model statistics are shaped by the underlying state and an exogenous control input, which influence the observations' quality. Exploiting an innovations approach, an approximate minimum mean-squared error (MMSE) filter is derived to estimate the Markov chain system state. To optimize the control strategy, the associated mean-squared error is used as an optimization criterion in"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1312.2039","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2013-12-06T23:57:45Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"d16c5f883884ea629a1a22bfb35a109fb1053ecbe1c1db680c50801d2764f00f","abstract_canon_sha256":"79ad4e673d2bd3f5966d0e31053d0adf5bf2f600e766b2c5a9cf49c628d54cfc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:45:57.608225Z","signature_b64":"hcagIqxk+q/dBiSK7ZfXI9KyKxHzu+cvjjLtHfOiS/orjDi8yF+QOeNG3aGeCoHfXZqHNgRqxttgNXQwnAzaBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0171e4b9c5d669a671de4def36d18690d2f3181a24b369bb1836a462cff448c5","last_reissued_at":"2026-05-18T01:45:57.607765Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:45:57.607765Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Active Classification for POMDPs: a Kalman-like State Estimator","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.SY","authors_text":"Daphney-Stavroula Zois, Marco Levorato, Urbashi Mitra","submitted_at":"2013-12-06T23:57:45Z","abstract_excerpt":"The problem of state tracking with active observation control is considered for a system modeled by a discrete-time, finite-state Markov chain observed through conditionally Gaussian measurement vectors. The measurement model statistics are shaped by the underlying state and an exogenous control input, which influence the observations' quality. Exploiting an innovations approach, an approximate minimum mean-squared error (MMSE) filter is derived to estimate the Markov chain system state. To optimize the control strategy, the associated mean-squared error is used as an optimization criterion in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1312.2039","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1312.2039","created_at":"2026-05-18T01:45:57.607835+00:00"},{"alias_kind":"arxiv_version","alias_value":"1312.2039v1","created_at":"2026-05-18T01:45:57.607835+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1312.2039","created_at":"2026-05-18T01:45:57.607835+00:00"},{"alias_kind":"pith_short_12","alias_value":"AFY6JOOF2ZU2","created_at":"2026-05-18T12:27:38.830355+00:00"},{"alias_kind":"pith_short_16","alias_value":"AFY6JOOF2ZU2M4O6","created_at":"2026-05-18T12:27:38.830355+00:00"},{"alias_kind":"pith_short_8","alias_value":"AFY6JOOF","created_at":"2026-05-18T12:27:38.830355+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AFY6JOOF2ZU2M4O6JXXTNUMGSD","json":"https://pith.science/pith/AFY6JOOF2ZU2M4O6JXXTNUMGSD.json","graph_json":"https://pith.science/api/pith-number/AFY6JOOF2ZU2M4O6JXXTNUMGSD/graph.json","events_json":"https://pith.science/api/pith-number/AFY6JOOF2ZU2M4O6JXXTNUMGSD/events.json","paper":"https://pith.science/paper/AFY6JOOF"},"agent_actions":{"view_html":"https://pith.science/pith/AFY6JOOF2ZU2M4O6JXXTNUMGSD","download_json":"https://pith.science/pith/AFY6JOOF2ZU2M4O6JXXTNUMGSD.json","view_paper":"https://pith.science/paper/AFY6JOOF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1312.2039&json=true","fetch_graph":"https://pith.science/api/pith-number/AFY6JOOF2ZU2M4O6JXXTNUMGSD/graph.json","fetch_events":"https://pith.science/api/pith-number/AFY6JOOF2ZU2M4O6JXXTNUMGSD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AFY6JOOF2ZU2M4O6JXXTNUMGSD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AFY6JOOF2ZU2M4O6JXXTNUMGSD/action/storage_attestation","attest_author":"https://pith.science/pith/AFY6JOOF2ZU2M4O6JXXTNUMGSD/action/author_attestation","sign_citation":"https://pith.science/pith/AFY6JOOF2ZU2M4O6JXXTNUMGSD/action/citation_signature","submit_replication":"https://pith.science/pith/AFY6JOOF2ZU2M4O6JXXTNUMGSD/action/replication_record"}},"created_at":"2026-05-18T01:45:57.607835+00:00","updated_at":"2026-05-18T01:45:57.607835+00:00"}