{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:OQVYDYPJO7M6GUF2HAD3CHNB4K","short_pith_number":"pith:OQVYDYPJ","canonical_record":{"source":{"id":"1702.05663","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T22:15:25Z","cross_cats_sorted":[],"title_canon_sha256":"7408b23159c760ab7fa78d7930e7a47f80524b126ea106e7b070f06957b02c17","abstract_canon_sha256":"a3faa3eb6dd04610eff3ece8dc10ba6185975ba1efb4d73ca98cecadc584c19c"},"schema_version":"1.0"},"canonical_sha256":"742b81e1e977d9e350ba3807b11da1e2be3f57b702e6048ac677057b488e3c9c","source":{"kind":"arxiv","id":"1702.05663","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.05663","created_at":"2026-05-18T00:50:25Z"},{"alias_kind":"arxiv_version","alias_value":"1702.05663v1","created_at":"2026-05-18T00:50:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.05663","created_at":"2026-05-18T00:50:25Z"},{"alias_kind":"pith_short_12","alias_value":"OQVYDYPJO7M6","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_16","alias_value":"OQVYDYPJO7M6GUF2","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_8","alias_value":"OQVYDYPJ","created_at":"2026-05-18T12:31:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:OQVYDYPJO7M6GUF2HAD3CHNB4K","target":"record","payload":{"canonical_record":{"source":{"id":"1702.05663","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T22:15:25Z","cross_cats_sorted":[],"title_canon_sha256":"7408b23159c760ab7fa78d7930e7a47f80524b126ea106e7b070f06957b02c17","abstract_canon_sha256":"a3faa3eb6dd04610eff3ece8dc10ba6185975ba1efb4d73ca98cecadc584c19c"},"schema_version":"1.0"},"canonical_sha256":"742b81e1e977d9e350ba3807b11da1e2be3f57b702e6048ac677057b488e3c9c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:50:25.783373Z","signature_b64":"TchfwywQiKPPD7+exw5d+0Q0Dbf9QgdgVjtfUaL0XtB+6xcojvlB7d9lsdB+HX/yEWDxM0C4TwqtDwWKHpzUBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"742b81e1e977d9e350ba3807b11da1e2be3f57b702e6048ac677057b488e3c9c","last_reissued_at":"2026-05-18T00:50:25.782606Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:50:25.782606Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1702.05663","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":"2026-05-18T00:50:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TWJWKT/biXu3XJQuIpnokksa5P6+e412eXU6pgw+XkL3Rlr/nlDLZ7dmMQva8gIeXZCtbzihtis/1XygBp7RCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T10:01:40.634302Z"},"content_sha256":"742f0a31f6db66f1d13ec84cc96b0ed05249302ca32e527481e9fcbaa525f55c","schema_version":"1.0","event_id":"sha256:742f0a31f6db66f1d13ec84cc96b0ed05249302ca32e527481e9fcbaa525f55c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:OQVYDYPJO7M6GUF2HAD3CHNB4K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Game Imitation: Deep Supervised Convolutional Networks for Quick Video Game AI","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Darvin Yi, Zhao Chen","submitted_at":"2017-02-18T22:15:25Z","abstract_excerpt":"We present a vision-only model for gaming AI which uses a late integration deep convolutional network architecture trained in a purely supervised imitation learning context. Although state-of-the-art deep learning models for video game tasks generally rely on more complex methods such as deep-Q learning, we show that a supervised model which requires substantially fewer resources and training time can already perform well at human reaction speeds on the N64 classic game Super Smash Bros. We frame our learning task as a 30-class classification problem, and our CNN model achieves 80% top-1 and 9"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.05663","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":"2026-05-18T00:50:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AZL0SlPWcXQKa8kfrradbcS5daI8ZjPgD2RDhs2pnzjAM4GidGZqpiflmsiXLbsfB55ytciUfjrmd32vVqt7CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T10:01:40.634668Z"},"content_sha256":"eed03b4ded91878d3037b0c276d953c9fe5701912a585859eb3facf2f256e06f","schema_version":"1.0","event_id":"sha256:eed03b4ded91878d3037b0c276d953c9fe5701912a585859eb3facf2f256e06f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OQVYDYPJO7M6GUF2HAD3CHNB4K/bundle.json","state_url":"https://pith.science/pith/OQVYDYPJO7M6GUF2HAD3CHNB4K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OQVYDYPJO7M6GUF2HAD3CHNB4K/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":"2026-06-03T10:01:40Z","links":{"resolver":"https://pith.science/pith/OQVYDYPJO7M6GUF2HAD3CHNB4K","bundle":"https://pith.science/pith/OQVYDYPJO7M6GUF2HAD3CHNB4K/bundle.json","state":"https://pith.science/pith/OQVYDYPJO7M6GUF2HAD3CHNB4K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OQVYDYPJO7M6GUF2HAD3CHNB4K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:OQVYDYPJO7M6GUF2HAD3CHNB4K","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":"a3faa3eb6dd04610eff3ece8dc10ba6185975ba1efb4d73ca98cecadc584c19c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T22:15:25Z","title_canon_sha256":"7408b23159c760ab7fa78d7930e7a47f80524b126ea106e7b070f06957b02c17"},"schema_version":"1.0","source":{"id":"1702.05663","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.05663","created_at":"2026-05-18T00:50:25Z"},{"alias_kind":"arxiv_version","alias_value":"1702.05663v1","created_at":"2026-05-18T00:50:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.05663","created_at":"2026-05-18T00:50:25Z"},{"alias_kind":"pith_short_12","alias_value":"OQVYDYPJO7M6","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_16","alias_value":"OQVYDYPJO7M6GUF2","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_8","alias_value":"OQVYDYPJ","created_at":"2026-05-18T12:31:34Z"}],"graph_snapshots":[{"event_id":"sha256:eed03b4ded91878d3037b0c276d953c9fe5701912a585859eb3facf2f256e06f","target":"graph","created_at":"2026-05-18T00:50:25Z","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":"We present a vision-only model for gaming AI which uses a late integration deep convolutional network architecture trained in a purely supervised imitation learning context. Although state-of-the-art deep learning models for video game tasks generally rely on more complex methods such as deep-Q learning, we show that a supervised model which requires substantially fewer resources and training time can already perform well at human reaction speeds on the N64 classic game Super Smash Bros. We frame our learning task as a 30-class classification problem, and our CNN model achieves 80% top-1 and 9","authors_text":"Darvin Yi, Zhao Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T22:15:25Z","title":"The Game Imitation: Deep Supervised Convolutional Networks for Quick Video Game AI"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.05663","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":"sha256:742f0a31f6db66f1d13ec84cc96b0ed05249302ca32e527481e9fcbaa525f55c","target":"record","created_at":"2026-05-18T00:50:25Z","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":"a3faa3eb6dd04610eff3ece8dc10ba6185975ba1efb4d73ca98cecadc584c19c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T22:15:25Z","title_canon_sha256":"7408b23159c760ab7fa78d7930e7a47f80524b126ea106e7b070f06957b02c17"},"schema_version":"1.0","source":{"id":"1702.05663","kind":"arxiv","version":1}},"canonical_sha256":"742b81e1e977d9e350ba3807b11da1e2be3f57b702e6048ac677057b488e3c9c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"742b81e1e977d9e350ba3807b11da1e2be3f57b702e6048ac677057b488e3c9c","first_computed_at":"2026-05-18T00:50:25.782606Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:50:25.782606Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TchfwywQiKPPD7+exw5d+0Q0Dbf9QgdgVjtfUaL0XtB+6xcojvlB7d9lsdB+HX/yEWDxM0C4TwqtDwWKHpzUBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:50:25.783373Z","signed_message":"canonical_sha256_bytes"},"source_id":"1702.05663","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:742f0a31f6db66f1d13ec84cc96b0ed05249302ca32e527481e9fcbaa525f55c","sha256:eed03b4ded91878d3037b0c276d953c9fe5701912a585859eb3facf2f256e06f"],"state_sha256":"e8f2e827e98a91286e07df630a13002879380f79d0239721ac9f25c1c6e7a5b5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uTLoQrRQJpLuombvFck3C7StbbITZQOUcOD0cUw38vTn9RfeqLGQkQ1cb0lWiA5vrYYevroBB+Fx3oP4jK/mCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T10:01:40.636655Z","bundle_sha256":"31f87d8dbc09accb698404ef9036a20b6ea7ddd8a0033e8a7ca3dd9ba9cec33d"}}