{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QKCIVAN73PCSN3LPMFE3ZUIUSJ","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":"705ef9154ed9d0e79d90db7deb6188a2dd95d5de638aa767b941383a3a5c611a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-03-13T00:30:09Z","title_canon_sha256":"64d960afc00200c7f8866318f0b534b9dba0477c29e14922fd292e84fce4d025"},"schema_version":"1.0","source":{"id":"2403.08152","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.08152","created_at":"2026-07-05T11:49:45Z"},{"alias_kind":"arxiv_version","alias_value":"2403.08152v2","created_at":"2026-07-05T11:49:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.08152","created_at":"2026-07-05T11:49:45Z"},{"alias_kind":"pith_short_12","alias_value":"QKCIVAN73PCS","created_at":"2026-07-05T11:49:45Z"},{"alias_kind":"pith_short_16","alias_value":"QKCIVAN73PCSN3LP","created_at":"2026-07-05T11:49:45Z"},{"alias_kind":"pith_short_8","alias_value":"QKCIVAN7","created_at":"2026-07-05T11:49:45Z"}],"graph_snapshots":[{"event_id":"sha256:3a638c8c413e2450a674e706ae4e244c513a21b7c25fbbe373e5d3cf8393b728","target":"graph","created_at":"2026-07-05T11:49:45Z","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/2403.08152/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"High-speed online trajectory planning for UAVs poses a significant challenge due to the need for precise modeling of complex dynamics while also being constrained by computational limitations. This paper presents a multi-fidelity reinforcement learning method (MFRL) that aims to effectively create a realistic dynamics model and simultaneously train a planning policy that can be readily deployed in real-time applications. The proposed method involves the co-training of a planning policy and a reward estimator; the latter predicts the performance of the policy's output and is trained efficiently","authors_text":"Geoffrey Wang, Gilhyun Ryou, Sertac Karaman","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-03-13T00:30:09Z","title":"Multi-Fidelity Reinforcement Learning for Time-Optimal Quadrotor Re-planning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.08152","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":"sha256:353b2c15aa5dc4302c1d43997003b75784ea7f3d1dc6ad2dc1bb327cf4049de7","target":"record","created_at":"2026-07-05T11:49:45Z","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":"705ef9154ed9d0e79d90db7deb6188a2dd95d5de638aa767b941383a3a5c611a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-03-13T00:30:09Z","title_canon_sha256":"64d960afc00200c7f8866318f0b534b9dba0477c29e14922fd292e84fce4d025"},"schema_version":"1.0","source":{"id":"2403.08152","kind":"arxiv","version":2}},"canonical_sha256":"82848a81bfdbc526ed6f6149bcd114926d0397835b2f71332b910e174e29d229","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"82848a81bfdbc526ed6f6149bcd114926d0397835b2f71332b910e174e29d229","first_computed_at":"2026-07-05T11:49:45.152199Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:49:45.152199Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SJzyVHLWvh/xEsiKczbBI0je7/QgoV8sw+uQ6wimd0iIALdpeZyuMbOMsF6zsYH3I6kvobP6egw/YKEpoh5kDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:49:45.152654Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.08152","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:353b2c15aa5dc4302c1d43997003b75784ea7f3d1dc6ad2dc1bb327cf4049de7","sha256:3a638c8c413e2450a674e706ae4e244c513a21b7c25fbbe373e5d3cf8393b728"],"state_sha256":"46a05797ecc7dbc7e41816c4e0f915386807b1504247fc9ad19c835aedd2d366"}