Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T13:42:46.233335Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:1908.04573.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T13:42:46.233335Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
35 of 35 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 8edd8415-e090-4fc0-8768-de7cd50070c6 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Journal of Economic Dynamics and Control , 27(11):2207 – 2218, 2003
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 54dd1678-8039-454c-a204-fb8f519e9f2f · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 12880038-bed2-4c9f-8026-ae94f05958d4 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Deep Reinforcement Learning framework for Autonomous Driving
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 370b9111-e8aa-49ce-bdfc-b87cad7b422f · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Learning exploration/exploitation strategies for single trajectory reinforcement learning
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6798d111-1c15-4662-aca0-0f115115476c · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Papadimitriou and John N
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation de953e4b-b0bf-4ad4-b134-096eb2d0d40a · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Littman, and Andrew W
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4679c160-8724-4c08-9355-4d05b7468b00 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Foerster, Yannis M
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fbceb09e-f765-4f38-8f17-39fe0c10e8a0 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Multi-agent actor-critic for mixed cooperative-competitive environments
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a86e81aa-e180-4c75-9301-66acfc9d82ea · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9475dbb1-f6a8-4ab0-a282-63396384c439 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Counterfactual data- fusion for online reinforcement learners
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 63e98418-2dd5-4b6b-8cd5-cb4556658431 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Gupta, Maxim Egorov, and Mykel J
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e24adfeb-cd8b-490b-8edd-61daded97683 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Reinforcement Learning and Markov Decision Processes , pages 3–42
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 362d6500-549b-4b35-8e84-aedd8ec5a9bf · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Hausknecht and Peter Stone
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9ef5cc7b-dd91-49ac-a099-09a709ca417e · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Reinforcement learning to play an optimal nash equilibrium in team markov games
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a27245f5-2580-44cb-b65a-df97e1580644 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking An algorithm for distributed reinforcement learning in cooperative multi-agent systems
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c044677d-4295-4b94-936d-514674742946 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Reinforcement Learning and Dynamic Programming Using Function Approximators
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 38387a55-f649-44cb-b148-3cd75afea5c5 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work
Reference 17
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18565ce6-2aeb-48bc-89e1-0c7b972ef5d1 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Sutton, David A
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a39064e8-b6d7-4928-b4e0-4c18027758a3 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work
Reference 19
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f869ce81-7077-4e59-afbb-1e32c262aa19 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Riedmiller
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 866a8033-9635-4e5d-be76-3d3867f939cf · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Multi-agent sys- tems by incremental gradient reinforcement learning
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2cb127e6-adf7-4385-94ae-267bec94bbc4 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Playing Atari with Deep Reinforcement Learning
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 08f6b8c8-0db3-4cf5-b2db-ef289ee903f8 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Lillicrap, Jonathan J
Reference 23
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 77a671df-d574-42da-acc8-0da3f11eac35 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Carlos Garcia-Monco, Elena Astigarraga, Ainara Gonzalez, and Jordan Grafman
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c94113be-6588-4395-a970-8d932bb666f8 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work
Reference 25
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7a592191-4895-4e07-9653-3345cd79495f · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking A softmin-based neural model for causal reason- ing
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2f97b108-3462-4268-b618-7076a84ce547 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Kingma and Jimmy Ba
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d9c3d5bc-d632-482e-8e23-541e7b44e4e7 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Stewart, and Jimeng Sun
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6236c071-5416-4035-8443-5526c41ba023 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Cooperative multi-agent control using deep reinforcement learning
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f21a3529-4c2f-41fa-8f6c-339389ca3b12 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 55298849-d929-4f11-81ee-a652f369ab19 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Causal inference in statistics: An overview
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 722d6eeb-fca0-4456-8d74-21ba7dac79cc · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Causal inference based on counterfactuals
Reference 32
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6299355d-f805-4d32-adda-feff392c1364 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work
Reference 33
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 76ac22de-a8df-42fb-b01b-0288f874fac2 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications
Reference 34
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 13ee506f-08f8-4897-b7e9-6c960041cc10 · outbound
Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking WOLPERT and KAGAN TUMER.Optimal Payoff Functions for Members of Collectives , pages 355–369
Reference 35
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
No inbound Pith citation observations are available.