{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:IZHRMWAII5G3V3HO4S4QOYTOQ2","short_pith_number":"pith:IZHRMWAI","canonical_record":{"source":{"id":"2504.06721","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-09T09:20:37Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"349045af226e7702ef15d6220d0022a867d52e2ff72d989f9e19352244e9da78","abstract_canon_sha256":"b94237ed2fdd62d75cbd9aaf54d7f046f18b2513b33ca739aa4d1575469f14e4"},"schema_version":"1.0"},"canonical_sha256":"464f165808474dbaeceee4b907626e86a1a6f47951b374099af38068b9d04855","source":{"kind":"arxiv","id":"2504.06721","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.06721","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"arxiv_version","alias_value":"2504.06721v1","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.06721","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"pith_short_12","alias_value":"IZHRMWAII5G3","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"pith_short_16","alias_value":"IZHRMWAII5G3V3HO","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"pith_short_8","alias_value":"IZHRMWAI","created_at":"2026-07-05T10:46:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:IZHRMWAII5G3V3HO4S4QOYTOQ2","target":"record","payload":{"canonical_record":{"source":{"id":"2504.06721","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-09T09:20:37Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"349045af226e7702ef15d6220d0022a867d52e2ff72d989f9e19352244e9da78","abstract_canon_sha256":"b94237ed2fdd62d75cbd9aaf54d7f046f18b2513b33ca739aa4d1575469f14e4"},"schema_version":"1.0"},"canonical_sha256":"464f165808474dbaeceee4b907626e86a1a6f47951b374099af38068b9d04855","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:46:44.651692Z","signature_b64":"b1hl3Jni6YqARZaQF9qy01OCiOomL1bLBCJch4h3Btqy+S7En4+ZL6SX/l4Gx0YZiP/afedNJr4eZZodAbKrDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"464f165808474dbaeceee4b907626e86a1a6f47951b374099af38068b9d04855","last_reissued_at":"2026-07-05T10:46:44.651178Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:46:44.651178Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.06721","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":"2026-07-05T10:46:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RQs3JdpgNTs/0UsQxQ+3kKESm8HqmOMrHF/4XRVJ9W4GeIoWjeKGFGEYhD4IpnLXquYiL2pXSGX7de1nrjJZBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T00:50:53.338354Z"},"content_sha256":"2f143fa51f3120211bf392e7e51ed83b12ddb886123c3c70c6b33523eb240dc3","schema_version":"1.0","event_id":"sha256:2f143fa51f3120211bf392e7e51ed83b12ddb886123c3c70c6b33523eb240dc3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:IZHRMWAII5G3V3HO4S4QOYTOQ2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning global control of underactuated systems with Model-Based Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Alberto Dalla Libera, Diego Romeres, Giulio Giacomuzzo, Marco Cal\\`i, Niccol\\`o Turcato, Ruggero Carli","submitted_at":"2025-04-09T09:20:37Z","abstract_excerpt":"This short paper describes our proposed solution for the third edition of the \"AI Olympics with RealAIGym\" competition, held at ICRA 2025. We employed Monte-Carlo Probabilistic Inference for Learning Control (MC-PILCO), an MBRL algorithm recognized for its exceptional data efficiency across various low-dimensional robotic tasks, including cart-pole, ball \\& plate, and Furuta pendulum systems. MC-PILCO optimizes a system dynamics model using interaction data, enabling policy refinement through simulation rather than direct system data optimization. This approach has proven highly effective in p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.06721","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/2504.06721/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":"2026-07-05T10:46:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e6Bl1fp8hJ7u/Rw+zhhLp2YcJBoBnWjheUrVak1CqwM6o+GYLROA6gUCnkmvFQ8drbzA2/D4LQcvKpJFXKOXAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T00:50:53.338733Z"},"content_sha256":"afc8178fc9d2f14b73247bcb9f4afa27b65be78f7c769a7fe3ff6fd2868f601b","schema_version":"1.0","event_id":"sha256:afc8178fc9d2f14b73247bcb9f4afa27b65be78f7c769a7fe3ff6fd2868f601b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IZHRMWAII5G3V3HO4S4QOYTOQ2/bundle.json","state_url":"https://pith.science/pith/IZHRMWAII5G3V3HO4S4QOYTOQ2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IZHRMWAII5G3V3HO4S4QOYTOQ2/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":"2026-07-12T00:50:53Z","links":{"resolver":"https://pith.science/pith/IZHRMWAII5G3V3HO4S4QOYTOQ2","bundle":"https://pith.science/pith/IZHRMWAII5G3V3HO4S4QOYTOQ2/bundle.json","state":"https://pith.science/pith/IZHRMWAII5G3V3HO4S4QOYTOQ2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IZHRMWAII5G3V3HO4S4QOYTOQ2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:IZHRMWAII5G3V3HO4S4QOYTOQ2","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":"b94237ed2fdd62d75cbd9aaf54d7f046f18b2513b33ca739aa4d1575469f14e4","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-09T09:20:37Z","title_canon_sha256":"349045af226e7702ef15d6220d0022a867d52e2ff72d989f9e19352244e9da78"},"schema_version":"1.0","source":{"id":"2504.06721","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.06721","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"arxiv_version","alias_value":"2504.06721v1","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.06721","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"pith_short_12","alias_value":"IZHRMWAII5G3","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"pith_short_16","alias_value":"IZHRMWAII5G3V3HO","created_at":"2026-07-05T10:46:44Z"},{"alias_kind":"pith_short_8","alias_value":"IZHRMWAI","created_at":"2026-07-05T10:46:44Z"}],"graph_snapshots":[{"event_id":"sha256:afc8178fc9d2f14b73247bcb9f4afa27b65be78f7c769a7fe3ff6fd2868f601b","target":"graph","created_at":"2026-07-05T10:46:44Z","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/2504.06721/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This short paper describes our proposed solution for the third edition of the \"AI Olympics with RealAIGym\" competition, held at ICRA 2025. We employed Monte-Carlo Probabilistic Inference for Learning Control (MC-PILCO), an MBRL algorithm recognized for its exceptional data efficiency across various low-dimensional robotic tasks, including cart-pole, ball \\& plate, and Furuta pendulum systems. MC-PILCO optimizes a system dynamics model using interaction data, enabling policy refinement through simulation rather than direct system data optimization. This approach has proven highly effective in p","authors_text":"Alberto Dalla Libera, Diego Romeres, Giulio Giacomuzzo, Marco Cal\\`i, Niccol\\`o Turcato, Ruggero Carli","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-09T09:20:37Z","title":"Learning global control of underactuated systems with Model-Based Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.06721","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":"sha256:2f143fa51f3120211bf392e7e51ed83b12ddb886123c3c70c6b33523eb240dc3","target":"record","created_at":"2026-07-05T10:46:44Z","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":"b94237ed2fdd62d75cbd9aaf54d7f046f18b2513b33ca739aa4d1575469f14e4","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-09T09:20:37Z","title_canon_sha256":"349045af226e7702ef15d6220d0022a867d52e2ff72d989f9e19352244e9da78"},"schema_version":"1.0","source":{"id":"2504.06721","kind":"arxiv","version":1}},"canonical_sha256":"464f165808474dbaeceee4b907626e86a1a6f47951b374099af38068b9d04855","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"464f165808474dbaeceee4b907626e86a1a6f47951b374099af38068b9d04855","first_computed_at":"2026-07-05T10:46:44.651178Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:46:44.651178Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"b1hl3Jni6YqARZaQF9qy01OCiOomL1bLBCJch4h3Btqy+S7En4+ZL6SX/l4Gx0YZiP/afedNJr4eZZodAbKrDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:46:44.651692Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.06721","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2f143fa51f3120211bf392e7e51ed83b12ddb886123c3c70c6b33523eb240dc3","sha256:afc8178fc9d2f14b73247bcb9f4afa27b65be78f7c769a7fe3ff6fd2868f601b"],"state_sha256":"35666e87454f81e95ab6eb1e1479c556bb7ecab2c053a6f4617472fcc8f6c332"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"44dfC4XEpxHRaNZS1JHlq8bCZ5/1QVN/60vp2toF/NnWQjDAIGbk7MtyjijR7/c6nAe4MEdql5fCQ/r65jn5BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T00:50:53.342489Z","bundle_sha256":"d2a5285e1cf4e83f601c68684b7086de764f6d229c38e5ba68e7e67ab93a90e8"}}