{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:RCHETZUTEWEPFZ2WLKBHBRWGZ7","short_pith_number":"pith:RCHETZUT","canonical_record":{"source":{"id":"1607.07939","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2016-07-27T02:29:52Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"a0b012287368bb95446d0811cc124dbf18c9620c7f4cd427c876c3cb723bb756","abstract_canon_sha256":"1a9c4fc1b8601cef855143afc12a3b479443eb9f10949857334fa7aa4d73bd47"},"schema_version":"1.0"},"canonical_sha256":"888e49e6932588f2e7565a8270c6c6cfe29d85d763bc48e32cb332a6d4433ce9","source":{"kind":"arxiv","id":"1607.07939","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.07939","created_at":"2026-05-18T01:10:22Z"},{"alias_kind":"arxiv_version","alias_value":"1607.07939v1","created_at":"2026-05-18T01:10:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.07939","created_at":"2026-05-18T01:10:22Z"},{"alias_kind":"pith_short_12","alias_value":"RCHETZUTEWEP","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_16","alias_value":"RCHETZUTEWEPFZ2W","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_8","alias_value":"RCHETZUT","created_at":"2026-05-18T12:30:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:RCHETZUTEWEPFZ2WLKBHBRWGZ7","target":"record","payload":{"canonical_record":{"source":{"id":"1607.07939","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2016-07-27T02:29:52Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"a0b012287368bb95446d0811cc124dbf18c9620c7f4cd427c876c3cb723bb756","abstract_canon_sha256":"1a9c4fc1b8601cef855143afc12a3b479443eb9f10949857334fa7aa4d73bd47"},"schema_version":"1.0"},"canonical_sha256":"888e49e6932588f2e7565a8270c6c6cfe29d85d763bc48e32cb332a6d4433ce9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:10:22.898777Z","signature_b64":"G+yZR39t/GDXhV9SA0O44dwQ4NuE8/0wWZ32ogRYpfGf9dtwKLVWJXwUX+n6MvVVxNebxcC3oG58enMJLxDeCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"888e49e6932588f2e7565a8270c6c6cfe29d85d763bc48e32cb332a6d4433ce9","last_reissued_at":"2026-05-18T01:10:22.898303Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:10:22.898303Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1607.07939","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":"2026-05-18T01:10:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4pC+YQ0ydSYjiORcEGDC7amn3wdxkPQllQTOY012BX75hChU3RY0HQFIH/S9W9ZiuNugNb2HYSe02q+cVrBxDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T12:42:59.708893Z"},"content_sha256":"731b511016a84c926047f052d41684edbe3a56b3a2ed321c08bafaca97542a9f","schema_version":"1.0","event_id":"sha256:731b511016a84c926047f052d41684edbe3a56b3a2ed321c08bafaca97542a9f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:RCHETZUTEWEPFZ2WLKBHBRWGZ7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Sensorimotor Reinforcement Learning Framework for Physical Human-Robot Interaction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.RO","authors_text":"Ali Ghadirzadeh, Atsuto Maki, Danica Kragic, Judith B\\\"utepage, M{\\aa}rten Bj\\\"orkman","submitted_at":"2016-07-27T02:29:52Z","abstract_excerpt":"Modeling of physical human-robot collaborations is generally a challenging problem due to the unpredictive nature of human behavior. To address this issue, we present a data-efficient reinforcement learning framework which enables a robot to learn how to collaborate with a human partner. The robot learns the task from its own sensorimotor experiences in an unsupervised manner. The uncertainty of the human actions is modeled using Gaussian processes (GP) to implement action-value functions. Optimal action selection given the uncertain GP model is ensured by Bayesian optimization. We apply the f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.07939","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":"2026-05-18T01:10:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VFQAtbjexX3oNrm8vl37YF4ueiGY9R1rfcbbjl0JbnkM8i8hFskuWpk3nUeyEV2uJQk1rHdJ8LwWZ9DIyfiwAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T12:42:59.709524Z"},"content_sha256":"18f80fa1d78d5044d6873352e82c7f45df68f37a828d23ce56575b626bc7fda1","schema_version":"1.0","event_id":"sha256:18f80fa1d78d5044d6873352e82c7f45df68f37a828d23ce56575b626bc7fda1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RCHETZUTEWEPFZ2WLKBHBRWGZ7/bundle.json","state_url":"https://pith.science/pith/RCHETZUTEWEPFZ2WLKBHBRWGZ7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RCHETZUTEWEPFZ2WLKBHBRWGZ7/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":"2026-06-07T12:42:59Z","links":{"resolver":"https://pith.science/pith/RCHETZUTEWEPFZ2WLKBHBRWGZ7","bundle":"https://pith.science/pith/RCHETZUTEWEPFZ2WLKBHBRWGZ7/bundle.json","state":"https://pith.science/pith/RCHETZUTEWEPFZ2WLKBHBRWGZ7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RCHETZUTEWEPFZ2WLKBHBRWGZ7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:RCHETZUTEWEPFZ2WLKBHBRWGZ7","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":"1a9c4fc1b8601cef855143afc12a3b479443eb9f10949857334fa7aa4d73bd47","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2016-07-27T02:29:52Z","title_canon_sha256":"a0b012287368bb95446d0811cc124dbf18c9620c7f4cd427c876c3cb723bb756"},"schema_version":"1.0","source":{"id":"1607.07939","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.07939","created_at":"2026-05-18T01:10:22Z"},{"alias_kind":"arxiv_version","alias_value":"1607.07939v1","created_at":"2026-05-18T01:10:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.07939","created_at":"2026-05-18T01:10:22Z"},{"alias_kind":"pith_short_12","alias_value":"RCHETZUTEWEP","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_16","alias_value":"RCHETZUTEWEPFZ2W","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_8","alias_value":"RCHETZUT","created_at":"2026-05-18T12:30:41Z"}],"graph_snapshots":[{"event_id":"sha256:18f80fa1d78d5044d6873352e82c7f45df68f37a828d23ce56575b626bc7fda1","target":"graph","created_at":"2026-05-18T01:10:22Z","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":"Modeling of physical human-robot collaborations is generally a challenging problem due to the unpredictive nature of human behavior. To address this issue, we present a data-efficient reinforcement learning framework which enables a robot to learn how to collaborate with a human partner. The robot learns the task from its own sensorimotor experiences in an unsupervised manner. The uncertainty of the human actions is modeled using Gaussian processes (GP) to implement action-value functions. Optimal action selection given the uncertain GP model is ensured by Bayesian optimization. We apply the f","authors_text":"Ali Ghadirzadeh, Atsuto Maki, Danica Kragic, Judith B\\\"utepage, M{\\aa}rten Bj\\\"orkman","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2016-07-27T02:29:52Z","title":"A Sensorimotor Reinforcement Learning Framework for Physical Human-Robot Interaction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.07939","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":"sha256:731b511016a84c926047f052d41684edbe3a56b3a2ed321c08bafaca97542a9f","target":"record","created_at":"2026-05-18T01:10:22Z","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":"1a9c4fc1b8601cef855143afc12a3b479443eb9f10949857334fa7aa4d73bd47","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2016-07-27T02:29:52Z","title_canon_sha256":"a0b012287368bb95446d0811cc124dbf18c9620c7f4cd427c876c3cb723bb756"},"schema_version":"1.0","source":{"id":"1607.07939","kind":"arxiv","version":1}},"canonical_sha256":"888e49e6932588f2e7565a8270c6c6cfe29d85d763bc48e32cb332a6d4433ce9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"888e49e6932588f2e7565a8270c6c6cfe29d85d763bc48e32cb332a6d4433ce9","first_computed_at":"2026-05-18T01:10:22.898303Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:10:22.898303Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G+yZR39t/GDXhV9SA0O44dwQ4NuE8/0wWZ32ogRYpfGf9dtwKLVWJXwUX+n6MvVVxNebxcC3oG58enMJLxDeCg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:10:22.898777Z","signed_message":"canonical_sha256_bytes"},"source_id":"1607.07939","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:731b511016a84c926047f052d41684edbe3a56b3a2ed321c08bafaca97542a9f","sha256:18f80fa1d78d5044d6873352e82c7f45df68f37a828d23ce56575b626bc7fda1"],"state_sha256":"74c7f779c68a4cd6824e67ca555577c728866e7040bd1f16a069213da55d60d0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MhxUcm4epavpVRPje3dGQp8MnUBQGANW/2Yj7eZ/4/pFW9+jyrV1qpNSYYo9tBETu+Zro2w3u4AZ40mi7y7ZAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T12:42:59.712638Z","bundle_sha256":"a22904742218cc6bf11ce2909a249a0c5a34051f325827a2cec93a8eb329592c"}}