{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:RY7DK5MP3QLJB5ZOXXXZF6YMMP","short_pith_number":"pith:RY7DK5MP","canonical_record":{"source":{"id":"1705.06936","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-05-19T11:19:45Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"b6c8085bc80cd5c2138c93d0927c08c51787fa7327ed110f5cf8616d5a724d3b","abstract_canon_sha256":"47ae3b2ae993ef8bc4e5158301a5690654bf27ab98c359b995bf21bf95d9cc7f"},"schema_version":"1.0"},"canonical_sha256":"8e3e35758fdc1690f72ebdef92fb0c63f6a879ed8ae76918aca641c36475678c","source":{"kind":"arxiv","id":"1705.06936","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.06936","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"arxiv_version","alias_value":"1705.06936v1","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.06936","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"pith_short_12","alias_value":"RY7DK5MP3QLJ","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"RY7DK5MP3QLJB5ZO","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"RY7DK5MP","created_at":"2026-05-18T12:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:RY7DK5MP3QLJB5ZOXXXZF6YMMP","target":"record","payload":{"canonical_record":{"source":{"id":"1705.06936","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-05-19T11:19:45Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"b6c8085bc80cd5c2138c93d0927c08c51787fa7327ed110f5cf8616d5a724d3b","abstract_canon_sha256":"47ae3b2ae993ef8bc4e5158301a5690654bf27ab98c359b995bf21bf95d9cc7f"},"schema_version":"1.0"},"canonical_sha256":"8e3e35758fdc1690f72ebdef92fb0c63f6a879ed8ae76918aca641c36475678c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:31.839491Z","signature_b64":"d7NSN4zy3qGGp5MDUc2IRJrXphmKiNXaSCr+CrO4u001iLBV3yTYEL0cgFzqX4fnIn3/H0VEgKHlfNWXMxnJDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e3e35758fdc1690f72ebdef92fb0c63f6a879ed8ae76918aca641c36475678c","last_reissued_at":"2026-05-18T00:18:31.838903Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:31.838903Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1705.06936","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":"2026-05-18T00:18:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P6mvqNFQ6ZfwAivK5xp/IgZLkZFx7L2uy+KHgEBym30bQdeayBzmVCu9vx/EcbKAOal6csUXz7QU8+VRtGtZCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T23:02:12.493597Z"},"content_sha256":"6cd8dbca9a7c27544c198b54dc5c6425463fc636fc2fd9708e5d6cdfdc47fa87","schema_version":"1.0","event_id":"sha256:6cd8dbca9a7c27544c198b54dc5c6425463fc636fc2fd9708e5d6cdfdc47fa87"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:RY7DK5MP3QLJB5ZOXXXZF6YMMP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Atari games and Intel processors","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.DC","authors_text":"Henryk Michalewski, Maciej Klimek, Robert Adamski, Tomasz Grel","submitted_at":"2017-05-19T11:19:45Z","abstract_excerpt":"The asynchronous nature of the state-of-the-art reinforcement learning algorithms such as the Asynchronous Advantage Actor-Critic algorithm, makes them exceptionally suitable for CPU computations. However, given the fact that deep reinforcement learning often deals with interpreting visual information, a large part of the train and inference time is spent performing convolutions. In this work we present our results on learning strategies in Atari games using a Convolutional Neural Network, the Math Kernel Library and TensorFlow 0.11rc0 machine learning framework. We also analyze effects of asy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.06936","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":"2026-05-18T00:18:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cxV4dqfdIe+PmrrPd4noAgG3gd0fZZbDYQviZMB0k34ALdBTrD6o3DolwdicbL9NAD4NF7XrVsn3jzU/GwoEDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T23:02:12.493933Z"},"content_sha256":"a52d183adfa092e242f696eb88703f479a41a408c4e346c3a6a7d96059860db4","schema_version":"1.0","event_id":"sha256:a52d183adfa092e242f696eb88703f479a41a408c4e346c3a6a7d96059860db4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RY7DK5MP3QLJB5ZOXXXZF6YMMP/bundle.json","state_url":"https://pith.science/pith/RY7DK5MP3QLJB5ZOXXXZF6YMMP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RY7DK5MP3QLJB5ZOXXXZF6YMMP/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":"2026-06-21T23:02:12Z","links":{"resolver":"https://pith.science/pith/RY7DK5MP3QLJB5ZOXXXZF6YMMP","bundle":"https://pith.science/pith/RY7DK5MP3QLJB5ZOXXXZF6YMMP/bundle.json","state":"https://pith.science/pith/RY7DK5MP3QLJB5ZOXXXZF6YMMP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RY7DK5MP3QLJB5ZOXXXZF6YMMP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:RY7DK5MP3QLJB5ZOXXXZF6YMMP","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":"47ae3b2ae993ef8bc4e5158301a5690654bf27ab98c359b995bf21bf95d9cc7f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-05-19T11:19:45Z","title_canon_sha256":"b6c8085bc80cd5c2138c93d0927c08c51787fa7327ed110f5cf8616d5a724d3b"},"schema_version":"1.0","source":{"id":"1705.06936","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.06936","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"arxiv_version","alias_value":"1705.06936v1","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.06936","created_at":"2026-05-18T00:18:31Z"},{"alias_kind":"pith_short_12","alias_value":"RY7DK5MP3QLJ","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"RY7DK5MP3QLJB5ZO","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"RY7DK5MP","created_at":"2026-05-18T12:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:a52d183adfa092e242f696eb88703f479a41a408c4e346c3a6a7d96059860db4","target":"graph","created_at":"2026-05-18T00:18:31Z","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":"The asynchronous nature of the state-of-the-art reinforcement learning algorithms such as the Asynchronous Advantage Actor-Critic algorithm, makes them exceptionally suitable for CPU computations. However, given the fact that deep reinforcement learning often deals with interpreting visual information, a large part of the train and inference time is spent performing convolutions. In this work we present our results on learning strategies in Atari games using a Convolutional Neural Network, the Math Kernel Library and TensorFlow 0.11rc0 machine learning framework. We also analyze effects of asy","authors_text":"Henryk Michalewski, Maciej Klimek, Robert Adamski, Tomasz Grel","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-05-19T11:19:45Z","title":"Atari games and Intel processors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.06936","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":"sha256:6cd8dbca9a7c27544c198b54dc5c6425463fc636fc2fd9708e5d6cdfdc47fa87","target":"record","created_at":"2026-05-18T00:18:31Z","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":"47ae3b2ae993ef8bc4e5158301a5690654bf27ab98c359b995bf21bf95d9cc7f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-05-19T11:19:45Z","title_canon_sha256":"b6c8085bc80cd5c2138c93d0927c08c51787fa7327ed110f5cf8616d5a724d3b"},"schema_version":"1.0","source":{"id":"1705.06936","kind":"arxiv","version":1}},"canonical_sha256":"8e3e35758fdc1690f72ebdef92fb0c63f6a879ed8ae76918aca641c36475678c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8e3e35758fdc1690f72ebdef92fb0c63f6a879ed8ae76918aca641c36475678c","first_computed_at":"2026-05-18T00:18:31.838903Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:18:31.838903Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"d7NSN4zy3qGGp5MDUc2IRJrXphmKiNXaSCr+CrO4u001iLBV3yTYEL0cgFzqX4fnIn3/H0VEgKHlfNWXMxnJDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:18:31.839491Z","signed_message":"canonical_sha256_bytes"},"source_id":"1705.06936","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6cd8dbca9a7c27544c198b54dc5c6425463fc636fc2fd9708e5d6cdfdc47fa87","sha256:a52d183adfa092e242f696eb88703f479a41a408c4e346c3a6a7d96059860db4"],"state_sha256":"fb1af049016670aeab9bbe6a9632428191b9ea807be39494bc75b3b7f0d404e4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LHUOZPwIt1jpLL9eyTXT2IfARwzU5Ukj69qWvE2K0s+M3IGAS1YLWPqAYtyE97tWHG7SQ7M10lH1PT0OG5cwAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-21T23:02:12.495802Z","bundle_sha256":"4f650d2c3f66ec879c17a572c7613120ff62599a6608448c4c3bd9081649cefd"}}