{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:LSKZ7L3WKIBP3NWTU6CX6RXZBT","short_pith_number":"pith:LSKZ7L3W","canonical_record":{"source":{"id":"1307.5606","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2013-07-22T07:04:27Z","cross_cats_sorted":[],"title_canon_sha256":"6451cf95b1bd0fd2526d69f78dee53e8c253d6017859a5ac3e4c5f454aa914e5","abstract_canon_sha256":"16dd60e0b88f0030b8f8765defeb38b3110429eab8cf984184eb7204932b6c9d"},"schema_version":"1.0"},"canonical_sha256":"5c959faf765202fdb6d3a7857f46f90ccea37151328587c8d1dbec875f7d3d1b","source":{"kind":"arxiv","id":"1307.5606","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1307.5606","created_at":"2026-05-18T02:28:13Z"},{"alias_kind":"arxiv_version","alias_value":"1307.5606v2","created_at":"2026-05-18T02:28:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1307.5606","created_at":"2026-05-18T02:28:13Z"},{"alias_kind":"pith_short_12","alias_value":"LSKZ7L3WKIBP","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"LSKZ7L3WKIBP3NWT","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"LSKZ7L3W","created_at":"2026-05-18T12:27:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:LSKZ7L3WKIBP3NWTU6CX6RXZBT","target":"record","payload":{"canonical_record":{"source":{"id":"1307.5606","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2013-07-22T07:04:27Z","cross_cats_sorted":[],"title_canon_sha256":"6451cf95b1bd0fd2526d69f78dee53e8c253d6017859a5ac3e4c5f454aa914e5","abstract_canon_sha256":"16dd60e0b88f0030b8f8765defeb38b3110429eab8cf984184eb7204932b6c9d"},"schema_version":"1.0"},"canonical_sha256":"5c959faf765202fdb6d3a7857f46f90ccea37151328587c8d1dbec875f7d3d1b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:28:13.499958Z","signature_b64":"XWTqm63Ijoocb9FqpA4FL1XJLX8PgIScXRMca9uV6mskjIiyrfk2HH4h4SmgpdWEutfLq1A5w+QcrM3vElebBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5c959faf765202fdb6d3a7857f46f90ccea37151328587c8d1dbec875f7d3d1b","last_reissued_at":"2026-05-18T02:28:13.499270Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:28:13.499270Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1307.5606","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:28:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cycu29dUM+8p48yxWXNAP4Nsr3GAuvUw77jxIUN0Lnd0zfRY3iDmg8738oAUuoDkzKzXG5sblBDeqhyY992KBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:17:19.664608Z"},"content_sha256":"53136d1ee63a58e66ed4401799442ef20c9f6498d663432041e5f8fab034ff89","schema_version":"1.0","event_id":"sha256:53136d1ee63a58e66ed4401799442ef20c9f6498d663432041e5f8fab034ff89"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:LSKZ7L3WKIBP3NWTU6CX6RXZBT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Stochastic Target Games and Dynamic Programming via Regularized Viscosity Solutions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.PR","authors_text":"Bruno Bouchard (CREST, CEREMADE), Marcel Nutz","submitted_at":"2013-07-22T07:04:27Z","abstract_excerpt":"We study a class of stochastic target games where one player tries to find a strategy such that the state process almost-surely reaches a given target, no matter which action is chosen by the opponent. Our main result is a geometric dynamic programming principle which allows us to characterize the value function as the viscosity solution of a non-linear partial differential equation. Because abstract mea-surable selection arguments cannot be used in this context, the main obstacle is the construction of measurable almost-optimal strategies. We propose a novel approach where smooth supersolutio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1307.5606","kind":"arxiv","version":2},"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":"2026-05-18T02:28:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4OfZQnTy7x7aex9SUcFNA2Q392bU0FXgiaSef+Wvi2gV3BoV5J37t2gvTTQcOK7FrJfTgCAUjMOb6F6bwUs0Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:17:19.665308Z"},"content_sha256":"eb5dd5ac0bf35b534d5c234e3958ca5012a6db311189ace85e140de90e1dfc35","schema_version":"1.0","event_id":"sha256:eb5dd5ac0bf35b534d5c234e3958ca5012a6db311189ace85e140de90e1dfc35"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LSKZ7L3WKIBP3NWTU6CX6RXZBT/bundle.json","state_url":"https://pith.science/pith/LSKZ7L3WKIBP3NWTU6CX6RXZBT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LSKZ7L3WKIBP3NWTU6CX6RXZBT/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":"2026-05-25T18:17:19Z","links":{"resolver":"https://pith.science/pith/LSKZ7L3WKIBP3NWTU6CX6RXZBT","bundle":"https://pith.science/pith/LSKZ7L3WKIBP3NWTU6CX6RXZBT/bundle.json","state":"https://pith.science/pith/LSKZ7L3WKIBP3NWTU6CX6RXZBT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LSKZ7L3WKIBP3NWTU6CX6RXZBT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:LSKZ7L3WKIBP3NWTU6CX6RXZBT","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":"16dd60e0b88f0030b8f8765defeb38b3110429eab8cf984184eb7204932b6c9d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2013-07-22T07:04:27Z","title_canon_sha256":"6451cf95b1bd0fd2526d69f78dee53e8c253d6017859a5ac3e4c5f454aa914e5"},"schema_version":"1.0","source":{"id":"1307.5606","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1307.5606","created_at":"2026-05-18T02:28:13Z"},{"alias_kind":"arxiv_version","alias_value":"1307.5606v2","created_at":"2026-05-18T02:28:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1307.5606","created_at":"2026-05-18T02:28:13Z"},{"alias_kind":"pith_short_12","alias_value":"LSKZ7L3WKIBP","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"LSKZ7L3WKIBP3NWT","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"LSKZ7L3W","created_at":"2026-05-18T12:27:51Z"}],"graph_snapshots":[{"event_id":"sha256:eb5dd5ac0bf35b534d5c234e3958ca5012a6db311189ace85e140de90e1dfc35","target":"graph","created_at":"2026-05-18T02:28:13Z","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 study a class of stochastic target games where one player tries to find a strategy such that the state process almost-surely reaches a given target, no matter which action is chosen by the opponent. Our main result is a geometric dynamic programming principle which allows us to characterize the value function as the viscosity solution of a non-linear partial differential equation. Because abstract mea-surable selection arguments cannot be used in this context, the main obstacle is the construction of measurable almost-optimal strategies. We propose a novel approach where smooth supersolutio","authors_text":"Bruno Bouchard (CREST, CEREMADE), Marcel Nutz","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2013-07-22T07:04:27Z","title":"Stochastic Target Games and Dynamic Programming via Regularized Viscosity Solutions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1307.5606","kind":"arxiv","version":2},"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":"sha256:53136d1ee63a58e66ed4401799442ef20c9f6498d663432041e5f8fab034ff89","target":"record","created_at":"2026-05-18T02:28:13Z","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":"16dd60e0b88f0030b8f8765defeb38b3110429eab8cf984184eb7204932b6c9d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2013-07-22T07:04:27Z","title_canon_sha256":"6451cf95b1bd0fd2526d69f78dee53e8c253d6017859a5ac3e4c5f454aa914e5"},"schema_version":"1.0","source":{"id":"1307.5606","kind":"arxiv","version":2}},"canonical_sha256":"5c959faf765202fdb6d3a7857f46f90ccea37151328587c8d1dbec875f7d3d1b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5c959faf765202fdb6d3a7857f46f90ccea37151328587c8d1dbec875f7d3d1b","first_computed_at":"2026-05-18T02:28:13.499270Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:28:13.499270Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XWTqm63Ijoocb9FqpA4FL1XJLX8PgIScXRMca9uV6mskjIiyrfk2HH4h4SmgpdWEutfLq1A5w+QcrM3vElebBA==","signature_status":"signed_v1","signed_at":"2026-05-18T02:28:13.499958Z","signed_message":"canonical_sha256_bytes"},"source_id":"1307.5606","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:53136d1ee63a58e66ed4401799442ef20c9f6498d663432041e5f8fab034ff89","sha256:eb5dd5ac0bf35b534d5c234e3958ca5012a6db311189ace85e140de90e1dfc35"],"state_sha256":"d0992f297cb26dc4667c0df55a94943d7982fb3359686674e0d04b4e74de88e2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J4kl4Lhgh9ObVRkE1AXEx2BI7tumVFSmWBbkl8W1QgUG4ExF3xzmXIUN6YjOz+N20K2Ewbx3fdKbytZlv42lBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T18:17:19.669822Z","bundle_sha256":"99cabdd50489b49942e8e992fa27872c507190e99a8dd94bc2e5c13b5552f2e1"}}