{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:OWSWQ33USXHY5BKQP2EUWR33RE","short_pith_number":"pith:OWSWQ33U","canonical_record":{"source":{"id":"2004.14547","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2020-04-30T02:23:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f42cd5a95bf2f2fc8938cfbf56f96852a86868d912d488daaa4b3dc2eb3e6845","abstract_canon_sha256":"c952bc8ed6b04b3d7f4802b4b4934b60e05d8c2afed6327e32e1f48f38efbff8"},"schema_version":"1.0"},"canonical_sha256":"75a5686f7495cf8e85507e894b477b89199b255d020a6bc979b62e6a8a02d2e2","source":{"kind":"arxiv","id":"2004.14547","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.14547","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"arxiv_version","alias_value":"2004.14547v3","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.14547","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"pith_short_12","alias_value":"OWSWQ33USXHY","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"pith_short_16","alias_value":"OWSWQ33USXHY5BKQ","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"pith_short_8","alias_value":"OWSWQ33U","created_at":"2026-07-05T11:28:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:OWSWQ33USXHY5BKQP2EUWR33RE","target":"record","payload":{"canonical_record":{"source":{"id":"2004.14547","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2020-04-30T02:23:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f42cd5a95bf2f2fc8938cfbf56f96852a86868d912d488daaa4b3dc2eb3e6845","abstract_canon_sha256":"c952bc8ed6b04b3d7f4802b4b4934b60e05d8c2afed6327e32e1f48f38efbff8"},"schema_version":"1.0"},"canonical_sha256":"75a5686f7495cf8e85507e894b477b89199b255d020a6bc979b62e6a8a02d2e2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:28:27.682935Z","signature_b64":"TbRfCY3h5nkS4xrRl57IzCYJAt5dyRTwcNZe8RsHXs7PjvNNxwv7D4os6AMw5UnUNgZaH1KnNIpjdItwJTYbAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"75a5686f7495cf8e85507e894b477b89199b255d020a6bc979b62e6a8a02d2e2","last_reissued_at":"2026-07-05T11:28:27.682459Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:28:27.682459Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2004.14547","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:28:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cDb0ymG0gBqH+7Nmlo5oBQWk/+N3cTAl6s5yk4HolUJ0/9fqIKMUob2NQr5O4zH40/BGke5HerritraXH/CMBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T03:24:00.712293Z"},"content_sha256":"9220d88bd56f33cee606f7cf4df15f2e4fca5af2221efc3b6b1fe2a29868b83d","schema_version":"1.0","event_id":"sha256:9220d88bd56f33cee606f7cf4df15f2e4fca5af2221efc3b6b1fe2a29868b83d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:OWSWQ33USXHY5BKQP2EUWR33RE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DSAC: Distributional Soft Actor-Critic for Risk-Sensitive Reinforcement Learning","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Jun Yang, Junyao Chen, Li Xia, Qianchuan Zhao, Xiaoteng Ma, Zhengyuan Zhou","submitted_at":"2020-04-30T02:23:15Z","abstract_excerpt":"We present Distributional Soft Actor-Critic (DSAC), a distributional reinforcement learning (RL) algorithm that combines the strengths of distributional information of accumulated rewards and entropy-driven exploration from Soft Actor-Critic (SAC) algorithm. DSAC models the randomness in both action and rewards, surpassing baseline performances on various continuous control tasks. Unlike standard approaches that solely maximize expected rewards, we propose a unified framework for risk-sensitive learning, one that optimizes the risk-related objective while balancing entropy to encourage explora"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.14547","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2004.14547/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":"2026-07-05T11:28:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dAbdr67Wmh484iuMfMj6y16XR05zubrBvvZN6lui7vk3pemmYJScqt/D/Bz5SDT3+xjvtGrP/qehGfhSD6C2DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T03:24:00.712912Z"},"content_sha256":"6414091a59939deb5a499e4085a2aaa06fc71d2bce8a32295a42b8c0af73b074","schema_version":"1.0","event_id":"sha256:6414091a59939deb5a499e4085a2aaa06fc71d2bce8a32295a42b8c0af73b074"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OWSWQ33USXHY5BKQP2EUWR33RE/bundle.json","state_url":"https://pith.science/pith/OWSWQ33USXHY5BKQP2EUWR33RE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OWSWQ33USXHY5BKQP2EUWR33RE/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":"2026-07-07T03:24:00Z","links":{"resolver":"https://pith.science/pith/OWSWQ33USXHY5BKQP2EUWR33RE","bundle":"https://pith.science/pith/OWSWQ33USXHY5BKQP2EUWR33RE/bundle.json","state":"https://pith.science/pith/OWSWQ33USXHY5BKQP2EUWR33RE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OWSWQ33USXHY5BKQP2EUWR33RE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:OWSWQ33USXHY5BKQP2EUWR33RE","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":"c952bc8ed6b04b3d7f4802b4b4934b60e05d8c2afed6327e32e1f48f38efbff8","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2020-04-30T02:23:15Z","title_canon_sha256":"f42cd5a95bf2f2fc8938cfbf56f96852a86868d912d488daaa4b3dc2eb3e6845"},"schema_version":"1.0","source":{"id":"2004.14547","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.14547","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"arxiv_version","alias_value":"2004.14547v3","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.14547","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"pith_short_12","alias_value":"OWSWQ33USXHY","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"pith_short_16","alias_value":"OWSWQ33USXHY5BKQ","created_at":"2026-07-05T11:28:27Z"},{"alias_kind":"pith_short_8","alias_value":"OWSWQ33U","created_at":"2026-07-05T11:28:27Z"}],"graph_snapshots":[{"event_id":"sha256:6414091a59939deb5a499e4085a2aaa06fc71d2bce8a32295a42b8c0af73b074","target":"graph","created_at":"2026-07-05T11:28:27Z","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/2004.14547/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present Distributional Soft Actor-Critic (DSAC), a distributional reinforcement learning (RL) algorithm that combines the strengths of distributional information of accumulated rewards and entropy-driven exploration from Soft Actor-Critic (SAC) algorithm. DSAC models the randomness in both action and rewards, surpassing baseline performances on various continuous control tasks. Unlike standard approaches that solely maximize expected rewards, we propose a unified framework for risk-sensitive learning, one that optimizes the risk-related objective while balancing entropy to encourage explora","authors_text":"Jun Yang, Junyao Chen, Li Xia, Qianchuan Zhao, Xiaoteng Ma, Zhengyuan Zhou","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2020-04-30T02:23:15Z","title":"DSAC: Distributional Soft Actor-Critic for Risk-Sensitive Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.14547","kind":"arxiv","version":3},"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":"sha256:9220d88bd56f33cee606f7cf4df15f2e4fca5af2221efc3b6b1fe2a29868b83d","target":"record","created_at":"2026-07-05T11:28:27Z","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":"c952bc8ed6b04b3d7f4802b4b4934b60e05d8c2afed6327e32e1f48f38efbff8","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2020-04-30T02:23:15Z","title_canon_sha256":"f42cd5a95bf2f2fc8938cfbf56f96852a86868d912d488daaa4b3dc2eb3e6845"},"schema_version":"1.0","source":{"id":"2004.14547","kind":"arxiv","version":3}},"canonical_sha256":"75a5686f7495cf8e85507e894b477b89199b255d020a6bc979b62e6a8a02d2e2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"75a5686f7495cf8e85507e894b477b89199b255d020a6bc979b62e6a8a02d2e2","first_computed_at":"2026-07-05T11:28:27.682459Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:28:27.682459Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TbRfCY3h5nkS4xrRl57IzCYJAt5dyRTwcNZe8RsHXs7PjvNNxwv7D4os6AMw5UnUNgZaH1KnNIpjdItwJTYbAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:28:27.682935Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.14547","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9220d88bd56f33cee606f7cf4df15f2e4fca5af2221efc3b6b1fe2a29868b83d","sha256:6414091a59939deb5a499e4085a2aaa06fc71d2bce8a32295a42b8c0af73b074"],"state_sha256":"29d255efdcf51f89b83e45c5e3116eefaa3a9393aa108df001aa87ec9c66eb01"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OVgQ2wqwfXvyviYkm78MD8VUXWf6n+1PtBcXbE+J3usCVQBuHrFOCxiSCqqTGd2VOtxfpRpY7N5IyabZBl/zCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T03:24:00.715743Z","bundle_sha256":"b113ee3a48ebb64c8785aa4f00ea39686277865865e2b3725edc696039814125"}}