{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:N3V4LSV6ERWMK4TW3NKXZKCB3H","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":"f0fd4aba9551f5ae1b524d70e206cc50b548f27bb53cfbb8890bfe17e98d31e5","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.TR","submitted_at":"2019-06-24T20:22:46Z","title_canon_sha256":"1a7859229ae3d9432c4f9e40f49f92b505cb806ab565f72c7b380adf20ae342e"},"schema_version":"1.0","source":{"id":"1906.11046","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.11046","created_at":"2026-05-17T23:42:10Z"},{"alias_kind":"arxiv_version","alias_value":"1906.11046v1","created_at":"2026-05-17T23:42:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.11046","created_at":"2026-05-17T23:42:10Z"},{"alias_kind":"pith_short_12","alias_value":"N3V4LSV6ERWM","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"N3V4LSV6ERWMK4TW","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"N3V4LSV6","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:e797002d18b5175bc74f60a2c27afb3967d353771b9b9b82171f136f796fc9c6","target":"graph","created_at":"2026-05-17T23:42:10Z","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":"Liquidation is the process of selling a large number of shares of one stock sequentially within a given time frame, taking into consideration the costs arising from market impact and a trader's risk aversion. The main challenge in optimizing liquidation is to find an appropriate modeling system that can incorporate the complexities of the stock market and generate practical trading strategies. In this paper, we propose to use multi-agent deep reinforcement learning model, which better captures high-level complexities comparing to various machine learning methods, such that agents can learn how","authors_text":"Wenhang Bao, Xiao-Yang Liu","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.TR","submitted_at":"2019-06-24T20:22:46Z","title":"Multi-Agent Deep Reinforcement Learning for Liquidation Strategy Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.11046","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:cdb7a5d4a010e3cfa8b76935f3b42423377c5a7d2e03a0e1ae5b13af5dc987ad","target":"record","created_at":"2026-05-17T23:42:10Z","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":"f0fd4aba9551f5ae1b524d70e206cc50b548f27bb53cfbb8890bfe17e98d31e5","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-fin.TR","submitted_at":"2019-06-24T20:22:46Z","title_canon_sha256":"1a7859229ae3d9432c4f9e40f49f92b505cb806ab565f72c7b380adf20ae342e"},"schema_version":"1.0","source":{"id":"1906.11046","kind":"arxiv","version":1}},"canonical_sha256":"6eebc5cabe246cc57276db557ca841d9c0128a1ce911ddbf954c6d30630732f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6eebc5cabe246cc57276db557ca841d9c0128a1ce911ddbf954c6d30630732f8","first_computed_at":"2026-05-17T23:42:10.080152Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:10.080152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BeTCvtcs6q9vQKxHv+XkEg+rLlGLh0tWhy9w8DgBic8L2yxcDYNgl/G2n/v8xpnKvwRQFFcU6RIi8HqtUjLJAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:10.080816Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.11046","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cdb7a5d4a010e3cfa8b76935f3b42423377c5a7d2e03a0e1ae5b13af5dc987ad","sha256:e797002d18b5175bc74f60a2c27afb3967d353771b9b9b82171f136f796fc9c6"],"state_sha256":"89dad8ddfd11763bea409a8542faab7d8957a01bd5a731f7f1596578e4c57b6c"}