{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:3LV56O3TCV6QH6TJ4YTOYA4N45","short_pith_number":"pith:3LV56O3T","canonical_record":{"source":{"id":"1902.02441","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-07T01:17:17Z","cross_cats_sorted":["cs.RO","stat.ML"],"title_canon_sha256":"d7858fd0c410995beb310403c19dc3d48ef1fe3a114a3e4ee0b2243dea97ac43","abstract_canon_sha256":"ef2761465963f7ac8939d4f378c9be29bd733553c264b43f1b04a9f3c8df9b6d"},"schema_version":"1.0"},"canonical_sha256":"daebdf3b73157d03fa69e626ec038de75f57f893cbdc9ed0eac00f872cfd7d9a","source":{"kind":"arxiv","id":"1902.02441","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.02441","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"arxiv_version","alias_value":"1902.02441v1","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.02441","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"pith_short_12","alias_value":"3LV56O3TCV6Q","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3LV56O3TCV6QH6TJ","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3LV56O3T","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:3LV56O3TCV6QH6TJ4YTOYA4N45","target":"record","payload":{"canonical_record":{"source":{"id":"1902.02441","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-07T01:17:17Z","cross_cats_sorted":["cs.RO","stat.ML"],"title_canon_sha256":"d7858fd0c410995beb310403c19dc3d48ef1fe3a114a3e4ee0b2243dea97ac43","abstract_canon_sha256":"ef2761465963f7ac8939d4f378c9be29bd733553c264b43f1b04a9f3c8df9b6d"},"schema_version":"1.0"},"canonical_sha256":"daebdf3b73157d03fa69e626ec038de75f57f893cbdc9ed0eac00f872cfd7d9a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:33.302524Z","signature_b64":"qCLGQLFnmxq9aSfohtILm0iBGw/3QW5TQ1mSPyf+3N81rMn4KLQKNpda70rjGNLKK0i93HbMrgsoSti1W3F1AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"daebdf3b73157d03fa69e626ec038de75f57f893cbdc9ed0eac00f872cfd7d9a","last_reissued_at":"2026-05-17T23:54:33.301832Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:33.301832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.02441","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":"2026-05-17T23:54:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+3523kN95bEoXFHiR1v6rxtA/CJW8I27gpEjC48I/l6uUDSR2LMdnmfQW5qgdfgcdx4J79tUgbbiMd6dUcMvDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T00:12:21.538419Z"},"content_sha256":"6d4896a9cf4600495d0929f2353cfe6b29d05508807d75dfcff884203817af78","schema_version":"1.0","event_id":"sha256:6d4896a9cf4600495d0929f2353cfe6b29d05508807d75dfcff884203817af78"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:3LV56O3TCV6QH6TJ4YTOYA4N45","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Artificial Intelligence for Prosthetics - challenge solutions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO","stat.ML"],"primary_cat":"cs.LG","authors_text":"Aditya Bhatt, Aleksandra Malysheva, Aleksei Shpilman, Anton Pechenko, Bo Zhou, Carmichael Ong, Daniel Kudenko, Evren Tumer, Fan Wang, Garrett Andersen, Hao Tian, Hongsheng Zeng, Ivan Sosin, Jennifer Hicks, Jeremy Watson, Jun Huang, Lance Rane, {\\L}ukasz Kidzi\\'nski, Marcel Salath\\'e, Mattias Ljungstr\\\"om, Minghui Qiu, Nihat Engin Toklu, Odd Rune Lykkeb{\\o}, Oleg Svidchenko, Oleksii Hrinchuk, Penghui Qi, Peng Peng, Pingchuan Ma, Pranav Shyam, Quan Yuan, Rongzhong Lian, Ruihan Yang, Rupesh Kumar Srivastava, Scott Delp, Sean F. Carroll, Sergey Kolesnikov, Sergey Levine, Sharada Prasanna Mohanty, Shauharda Khadka, Somdeb Majumdar, Wenxin Li, Wojciech Ja\\'skowski, Xu Hu, Yinyin Liu, Yunsheng Tian, Zach Dwiel, Zehong Hu, Zeyang Yu, Zhengfei Wang, Zhen Wang","submitted_at":"2019-02-07T01:17:17Z","abstract_excerpt":"In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a given time-varying velocity vector. Top participants were invited to describe their algorithms. In this work, we describe the challenge and present thirteen solutions that used deep reinforcement learning approaches. Many solutions use similar relaxations and heuristics, such as reward shaping, frame skipping, discretization of the action space, symmetry, and policy blending. However, each team implemented different mod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.02441","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:54:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eLN6GmTu1CyJdzoJeNVMSucZMxADZXNNO1nx9bcHnJOrvov9BbQPW2EqJatdkXKbRCMhDWKCDDN06oyeW3s0AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T00:12:21.539095Z"},"content_sha256":"c58060523e9f644e9918492d33c40fa556784e37a76d443d0bc881b8e5295ba1","schema_version":"1.0","event_id":"sha256:c58060523e9f644e9918492d33c40fa556784e37a76d443d0bc881b8e5295ba1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3LV56O3TCV6QH6TJ4YTOYA4N45/bundle.json","state_url":"https://pith.science/pith/3LV56O3TCV6QH6TJ4YTOYA4N45/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3LV56O3TCV6QH6TJ4YTOYA4N45/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":"2026-05-31T00:12:21Z","links":{"resolver":"https://pith.science/pith/3LV56O3TCV6QH6TJ4YTOYA4N45","bundle":"https://pith.science/pith/3LV56O3TCV6QH6TJ4YTOYA4N45/bundle.json","state":"https://pith.science/pith/3LV56O3TCV6QH6TJ4YTOYA4N45/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3LV56O3TCV6QH6TJ4YTOYA4N45/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:3LV56O3TCV6QH6TJ4YTOYA4N45","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":"ef2761465963f7ac8939d4f378c9be29bd733553c264b43f1b04a9f3c8df9b6d","cross_cats_sorted":["cs.RO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-07T01:17:17Z","title_canon_sha256":"d7858fd0c410995beb310403c19dc3d48ef1fe3a114a3e4ee0b2243dea97ac43"},"schema_version":"1.0","source":{"id":"1902.02441","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.02441","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"arxiv_version","alias_value":"1902.02441v1","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.02441","created_at":"2026-05-17T23:54:33Z"},{"alias_kind":"pith_short_12","alias_value":"3LV56O3TCV6Q","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"3LV56O3TCV6QH6TJ","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"3LV56O3T","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:c58060523e9f644e9918492d33c40fa556784e37a76d443d0bc881b8e5295ba1","target":"graph","created_at":"2026-05-17T23:54:33Z","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":"In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a given time-varying velocity vector. Top participants were invited to describe their algorithms. In this work, we describe the challenge and present thirteen solutions that used deep reinforcement learning approaches. Many solutions use similar relaxations and heuristics, such as reward shaping, frame skipping, discretization of the action space, symmetry, and policy blending. However, each team implemented different mod","authors_text":"Aditya Bhatt, Aleksandra Malysheva, Aleksei Shpilman, Anton Pechenko, Bo Zhou, Carmichael Ong, Daniel Kudenko, Evren Tumer, Fan Wang, Garrett Andersen, Hao Tian, Hongsheng Zeng, Ivan Sosin, Jennifer Hicks, Jeremy Watson, Jun Huang, Lance Rane, {\\L}ukasz Kidzi\\'nski, Marcel Salath\\'e, Mattias Ljungstr\\\"om, Minghui Qiu, Nihat Engin Toklu, Odd Rune Lykkeb{\\o}, Oleg Svidchenko, Oleksii Hrinchuk, Penghui Qi, Peng Peng, Pingchuan Ma, Pranav Shyam, Quan Yuan, Rongzhong Lian, Ruihan Yang, Rupesh Kumar Srivastava, Scott Delp, Sean F. Carroll, Sergey Kolesnikov, Sergey Levine, Sharada Prasanna Mohanty, Shauharda Khadka, Somdeb Majumdar, Wenxin Li, Wojciech Ja\\'skowski, Xu Hu, Yinyin Liu, Yunsheng Tian, Zach Dwiel, Zehong Hu, Zeyang Yu, Zhengfei Wang, Zhen Wang","cross_cats":["cs.RO","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-07T01:17:17Z","title":"Artificial Intelligence for Prosthetics - challenge solutions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.02441","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":"sha256:6d4896a9cf4600495d0929f2353cfe6b29d05508807d75dfcff884203817af78","target":"record","created_at":"2026-05-17T23:54:33Z","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":"ef2761465963f7ac8939d4f378c9be29bd733553c264b43f1b04a9f3c8df9b6d","cross_cats_sorted":["cs.RO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-07T01:17:17Z","title_canon_sha256":"d7858fd0c410995beb310403c19dc3d48ef1fe3a114a3e4ee0b2243dea97ac43"},"schema_version":"1.0","source":{"id":"1902.02441","kind":"arxiv","version":1}},"canonical_sha256":"daebdf3b73157d03fa69e626ec038de75f57f893cbdc9ed0eac00f872cfd7d9a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"daebdf3b73157d03fa69e626ec038de75f57f893cbdc9ed0eac00f872cfd7d9a","first_computed_at":"2026-05-17T23:54:33.301832Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:54:33.301832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qCLGQLFnmxq9aSfohtILm0iBGw/3QW5TQ1mSPyf+3N81rMn4KLQKNpda70rjGNLKK0i93HbMrgsoSti1W3F1AA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:54:33.302524Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.02441","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6d4896a9cf4600495d0929f2353cfe6b29d05508807d75dfcff884203817af78","sha256:c58060523e9f644e9918492d33c40fa556784e37a76d443d0bc881b8e5295ba1"],"state_sha256":"77d29a97ba70c606dcbf1bf1a2b55decfa652b759c705335026ee481356f06e7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qifwzzdsG0CbivVttL4ilWbTfFp55QPcST8XWajYECtXdrE3jLESi8qWn8+OHP4jr0lmw/XnZoZbkcUMlpaSDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T00:12:21.542416Z","bundle_sha256":"46ee4e1013b7181894de12324c0b19346078d9653d3e728dd39ce4c679b8d5e1"}}