{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:ORQLZIKMSVGJ56EY56XGJNOYIV","short_pith_number":"pith:ORQLZIKM","canonical_record":{"source":{"id":"1910.07224","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-16T09:07:43Z","cross_cats_sorted":["cs.RO","stat.ML"],"title_canon_sha256":"b4aa8743f966dc2aa3dfba9b663da8068f4f9bf35481de9e04e0d5933fb6aafb","abstract_canon_sha256":"79c97ec5447558bc8b77cfcf9b724a88165b1ee2db7de07364c47ca799ade9a3"},"schema_version":"1.0"},"canonical_sha256":"7460bca14c954c9ef898efae64b5d84568724e5250177f1e6602bafe46fd99a9","source":{"kind":"arxiv","id":"1910.07224","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.07224","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"arxiv_version","alias_value":"1910.07224v1","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.07224","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"pith_short_12","alias_value":"ORQLZIKMSVGJ","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"pith_short_16","alias_value":"ORQLZIKMSVGJ56EY","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"pith_short_8","alias_value":"ORQLZIKM","created_at":"2026-07-05T00:12:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:ORQLZIKMSVGJ56EY56XGJNOYIV","target":"record","payload":{"canonical_record":{"source":{"id":"1910.07224","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-16T09:07:43Z","cross_cats_sorted":["cs.RO","stat.ML"],"title_canon_sha256":"b4aa8743f966dc2aa3dfba9b663da8068f4f9bf35481de9e04e0d5933fb6aafb","abstract_canon_sha256":"79c97ec5447558bc8b77cfcf9b724a88165b1ee2db7de07364c47ca799ade9a3"},"schema_version":"1.0"},"canonical_sha256":"7460bca14c954c9ef898efae64b5d84568724e5250177f1e6602bafe46fd99a9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:12:33.919611Z","signature_b64":"PpFQB0lcsPjH+MncnQdFZIefcSmWZlSYeGbqWgWnIU5hjTD/PMI8Wx9G3crzdpUEw6MmLtTtik0ilJDP4sHSDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7460bca14c954c9ef898efae64b5d84568724e5250177f1e6602bafe46fd99a9","last_reissued_at":"2026-07-05T00:12:33.919240Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:12:33.919240Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1910.07224","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":"2026-07-05T00:12:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M7l9OAxbNbPnA1tswOMjzMxfydu/wvX/pTbqXD3TZEjiTSMGf1lof197HTYUfAk5EMTsBhr3ACt7OZhkxBgLDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T16:57:13.916660Z"},"content_sha256":"10a3ade168bd0ac5772a59cdde129dfa163d49d9df1832f489c82acaa0f639c0","schema_version":"1.0","event_id":"sha256:10a3ade168bd0ac5772a59cdde129dfa163d49d9df1832f489c82acaa0f639c0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:ORQLZIKMSVGJ56EY56XGJNOYIV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO","stat.ML"],"primary_cat":"cs.LG","authors_text":"C\\'edric Colas, Katja Hofmann, Pierre-Yves Oudeyer, R\\'emy Portelas","submitted_at":"2019-10-16T09:07:43Z","abstract_excerpt":"We consider the problem of how a teacher algorithm can enable an unknown Deep Reinforcement Learning (DRL) student to become good at a skill over a wide range of diverse environments. To do so, we study how a teacher algorithm can learn to generate a learning curriculum, whereby it sequentially samples parameters controlling a stochastic procedural generation of environments. Because it does not initially know the capacities of its student, a key challenge for the teacher is to discover which environments are easy, difficult or unlearnable, and in what order to propose them to maximize the eff"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.07224","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/1910.07224/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":"2026-07-05T00:12:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C8VTxphaUi93gx1mLJFTxpd5xL58JbfKa5g1TTTUfY3+v7W0s1SfQ+SJcdWw6m2sFa3Ky8N3LT9L4234nSQfBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T16:57:13.917034Z"},"content_sha256":"8ac3b892d92ddbb23540deec3544d42bf3399aded1af8bb67bc5e85c3f5e9197","schema_version":"1.0","event_id":"sha256:8ac3b892d92ddbb23540deec3544d42bf3399aded1af8bb67bc5e85c3f5e9197"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ORQLZIKMSVGJ56EY56XGJNOYIV/bundle.json","state_url":"https://pith.science/pith/ORQLZIKMSVGJ56EY56XGJNOYIV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ORQLZIKMSVGJ56EY56XGJNOYIV/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":"2026-07-08T16:57:13Z","links":{"resolver":"https://pith.science/pith/ORQLZIKMSVGJ56EY56XGJNOYIV","bundle":"https://pith.science/pith/ORQLZIKMSVGJ56EY56XGJNOYIV/bundle.json","state":"https://pith.science/pith/ORQLZIKMSVGJ56EY56XGJNOYIV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ORQLZIKMSVGJ56EY56XGJNOYIV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ORQLZIKMSVGJ56EY56XGJNOYIV","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":"79c97ec5447558bc8b77cfcf9b724a88165b1ee2db7de07364c47ca799ade9a3","cross_cats_sorted":["cs.RO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-16T09:07:43Z","title_canon_sha256":"b4aa8743f966dc2aa3dfba9b663da8068f4f9bf35481de9e04e0d5933fb6aafb"},"schema_version":"1.0","source":{"id":"1910.07224","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.07224","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"arxiv_version","alias_value":"1910.07224v1","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.07224","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"pith_short_12","alias_value":"ORQLZIKMSVGJ","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"pith_short_16","alias_value":"ORQLZIKMSVGJ56EY","created_at":"2026-07-05T00:12:33Z"},{"alias_kind":"pith_short_8","alias_value":"ORQLZIKM","created_at":"2026-07-05T00:12:33Z"}],"graph_snapshots":[{"event_id":"sha256:8ac3b892d92ddbb23540deec3544d42bf3399aded1af8bb67bc5e85c3f5e9197","target":"graph","created_at":"2026-07-05T00:12:33Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1910.07224/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We consider the problem of how a teacher algorithm can enable an unknown Deep Reinforcement Learning (DRL) student to become good at a skill over a wide range of diverse environments. To do so, we study how a teacher algorithm can learn to generate a learning curriculum, whereby it sequentially samples parameters controlling a stochastic procedural generation of environments. Because it does not initially know the capacities of its student, a key challenge for the teacher is to discover which environments are easy, difficult or unlearnable, and in what order to propose them to maximize the eff","authors_text":"C\\'edric Colas, Katja Hofmann, Pierre-Yves Oudeyer, R\\'emy Portelas","cross_cats":["cs.RO","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-16T09:07:43Z","title":"Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.07224","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":"sha256:10a3ade168bd0ac5772a59cdde129dfa163d49d9df1832f489c82acaa0f639c0","target":"record","created_at":"2026-07-05T00:12:33Z","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":"79c97ec5447558bc8b77cfcf9b724a88165b1ee2db7de07364c47ca799ade9a3","cross_cats_sorted":["cs.RO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-16T09:07:43Z","title_canon_sha256":"b4aa8743f966dc2aa3dfba9b663da8068f4f9bf35481de9e04e0d5933fb6aafb"},"schema_version":"1.0","source":{"id":"1910.07224","kind":"arxiv","version":1}},"canonical_sha256":"7460bca14c954c9ef898efae64b5d84568724e5250177f1e6602bafe46fd99a9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7460bca14c954c9ef898efae64b5d84568724e5250177f1e6602bafe46fd99a9","first_computed_at":"2026-07-05T00:12:33.919240Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:12:33.919240Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PpFQB0lcsPjH+MncnQdFZIefcSmWZlSYeGbqWgWnIU5hjTD/PMI8Wx9G3crzdpUEw6MmLtTtik0ilJDP4sHSDg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:12:33.919611Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.07224","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:10a3ade168bd0ac5772a59cdde129dfa163d49d9df1832f489c82acaa0f639c0","sha256:8ac3b892d92ddbb23540deec3544d42bf3399aded1af8bb67bc5e85c3f5e9197"],"state_sha256":"fee76c5151dae6122a64a1bca1d142b0d167c9c81b8f8fd2fdd8ea52707c1195"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E/lpSBZCBcXcr+4MiqEjuEQbHfmhCZ2/K8LXibwdKlV0Uxa6FMibWYNvj+/9KmgOKkZeLBXWMDkj63BRL9QnCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T16:57:13.919057Z","bundle_sha256":"d3d1de08f913606aa941c9468c7af3eec4135908a4699fbf62f12a34c4176910"}}