{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:XASH5H2H3QZPDR3RUEEE3NXKTK","short_pith_number":"pith:XASH5H2H","schema_version":"1.0","canonical_sha256":"b8247e9f47dc32f1c771a1084db6ea9ab7338903bb3c7bf079868a7690d33e3e","source":{"kind":"arxiv","id":"1709.07932","version":3},"attestation_state":"computed","paper":{"title":"Expanding Motor Skills through Relay Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"C. Karen Liu, Sehoon Ha, Visak C.V.Kumar","submitted_at":"2017-09-22T20:06:27Z","abstract_excerpt":"While the recent advances in deep reinforcement learning have achieved impressive results in learning motor skills, many of the trained policies are only capable within a limited set of initial states. We propose a technique to break down a complex robotic task to simpler subtasks and train them sequentially such that the robot can expand its existing skill set gradually. Our key idea is to build a tree of local control policies represented by neural networks, which we refer as Relay Neural Networks. Starting from the root policy that attempts to achieve the task from a small set of initial st"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1709.07932","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2017-09-22T20:06:27Z","cross_cats_sorted":[],"title_canon_sha256":"72d3cef9133164875a68139bf62cab80b8f1a575b01eb8c6d742b54e2d767de5","abstract_canon_sha256":"8d8e4833864d80bee2db9e7d98a1aa814ed68db48c1c534a504fff20825c3b87"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:35.432460Z","signature_b64":"quFsIZezIPDMcQVhZjivgV0ZDgLNOZGBw3l78sQ4OAQWyFat+xhxUUHmt3MIwjpm8xKt8c7/kUGDVUguO/tjDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b8247e9f47dc32f1c771a1084db6ea9ab7338903bb3c7bf079868a7690d33e3e","last_reissued_at":"2026-05-18T00:00:35.431906Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:35.431906Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Expanding Motor Skills through Relay Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"C. Karen Liu, Sehoon Ha, Visak C.V.Kumar","submitted_at":"2017-09-22T20:06:27Z","abstract_excerpt":"While the recent advances in deep reinforcement learning have achieved impressive results in learning motor skills, many of the trained policies are only capable within a limited set of initial states. We propose a technique to break down a complex robotic task to simpler subtasks and train them sequentially such that the robot can expand its existing skill set gradually. Our key idea is to build a tree of local control policies represented by neural networks, which we refer as Relay Neural Networks. Starting from the root policy that attempts to achieve the task from a small set of initial st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.07932","kind":"arxiv","version":3},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1709.07932","created_at":"2026-05-18T00:00:35.431986+00:00"},{"alias_kind":"arxiv_version","alias_value":"1709.07932v3","created_at":"2026-05-18T00:00:35.431986+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.07932","created_at":"2026-05-18T00:00:35.431986+00:00"},{"alias_kind":"pith_short_12","alias_value":"XASH5H2H3QZP","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_16","alias_value":"XASH5H2H3QZPDR3R","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_8","alias_value":"XASH5H2H","created_at":"2026-05-18T12:31:53.515858+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XASH5H2H3QZPDR3RUEEE3NXKTK","json":"https://pith.science/pith/XASH5H2H3QZPDR3RUEEE3NXKTK.json","graph_json":"https://pith.science/api/pith-number/XASH5H2H3QZPDR3RUEEE3NXKTK/graph.json","events_json":"https://pith.science/api/pith-number/XASH5H2H3QZPDR3RUEEE3NXKTK/events.json","paper":"https://pith.science/paper/XASH5H2H"},"agent_actions":{"view_html":"https://pith.science/pith/XASH5H2H3QZPDR3RUEEE3NXKTK","download_json":"https://pith.science/pith/XASH5H2H3QZPDR3RUEEE3NXKTK.json","view_paper":"https://pith.science/paper/XASH5H2H","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1709.07932&json=true","fetch_graph":"https://pith.science/api/pith-number/XASH5H2H3QZPDR3RUEEE3NXKTK/graph.json","fetch_events":"https://pith.science/api/pith-number/XASH5H2H3QZPDR3RUEEE3NXKTK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XASH5H2H3QZPDR3RUEEE3NXKTK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XASH5H2H3QZPDR3RUEEE3NXKTK/action/storage_attestation","attest_author":"https://pith.science/pith/XASH5H2H3QZPDR3RUEEE3NXKTK/action/author_attestation","sign_citation":"https://pith.science/pith/XASH5H2H3QZPDR3RUEEE3NXKTK/action/citation_signature","submit_replication":"https://pith.science/pith/XASH5H2H3QZPDR3RUEEE3NXKTK/action/replication_record"}},"created_at":"2026-05-18T00:00:35.431986+00:00","updated_at":"2026-05-18T00:00:35.431986+00:00"}