Paper Citation Record · LEDGER

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking

As of 20 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.

pith.paper-citation-record.v1
1908.04573 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:42:46.233335Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

verified exact0
verified fuzzy24
unresolved11
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External citation measurements

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Outbound references

Observation 8edd8415-e090-4fc0-8768-de7cd50070c6 · outbound

This paper cites Journal of Economic Dynamics and Control , 27(11):2207 – 2218, 2003.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Journal of Economic Dynamics and Control , 27(11):2207 – 2218, 2003

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.678473Z

Source-reported events for the cited work

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Observation 54dd1678-8039-454c-a204-fb8f519e9f2f · outbound

This paper cites an unresolved cited work.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:42:46.666863Z

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Observation 12880038-bed2-4c9f-8026-ae94f05958d4 · outbound

This paper cites Deep Reinforcement Learning framework for Autonomous Driving.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Deep Reinforcement Learning framework for Autonomous Driving

Reference 3

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Observation 370b9111-e8aa-49ce-bdfc-b87cad7b422f · outbound

This paper cites Learning exploration/exploitation strategies for single trajectory reinforcement learning.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Learning exploration/exploitation strategies for single trajectory reinforcement learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.655422Z

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Observation 6798d111-1c15-4662-aca0-0f115115476c · outbound

This paper cites Papadimitriou and John N.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Papadimitriou and John N

Reference 5

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Observation de953e4b-b0bf-4ad4-b134-096eb2d0d40a · outbound

This paper cites Littman, and Andrew W.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Littman, and Andrew W

Reference 6

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Observation 4679c160-8724-4c08-9355-4d05b7468b00 · outbound

This paper cites Foerster, Yannis M.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Foerster, Yannis M

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.621725Z

Source-reported events for the cited work

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Observation fbceb09e-f765-4f38-8f17-39fe0c10e8a0 · outbound

This paper cites Multi-agent actor-critic for mixed cooperative-competitive environments.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Multi-agent actor-critic for mixed cooperative-competitive environments

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.606911Z

Source-reported events for the cited work

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Observation a86e81aa-e180-4c75-9301-66acfc9d82ea · outbound

This paper cites Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson

Reference 9

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Source-reported events for the cited work

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Observation 9475dbb1-f6a8-4ab0-a282-63396384c439 · outbound

This paper cites Counterfactual data- fusion for online reinforcement learners.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Counterfactual data- fusion for online reinforcement learners

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.580700Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 63e98418-2dd5-4b6b-8cd5-cb4556658431 · outbound

This paper cites Gupta, Maxim Egorov, and Mykel J.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Gupta, Maxim Egorov, and Mykel J

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.568773Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e24adfeb-cd8b-490b-8edd-61daded97683 · outbound

This paper cites Reinforcement Learning and Markov Decision Processes , pages 3–42.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Reinforcement Learning and Markov Decision Processes , pages 3–42

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.555907Z

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Observation 362d6500-549b-4b35-8e84-aedd8ec5a9bf · outbound

This paper cites Hausknecht and Peter Stone.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Hausknecht and Peter Stone

Reference 13

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Source-reported events for the cited work

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Observation 9ef5cc7b-dd91-49ac-a099-09a709ca417e · outbound

This paper cites Reinforcement learning to play an optimal nash equilibrium in team markov games.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Reinforcement learning to play an optimal nash equilibrium in team markov games

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.529199Z

Source-reported events for the cited work

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Observation a27245f5-2580-44cb-b65a-df97e1580644 · outbound

This paper cites An algorithm for distributed reinforcement learning in cooperative multi-agent systems.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking An algorithm for distributed reinforcement learning in cooperative multi-agent systems

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.513247Z

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Observation c044677d-4295-4b94-936d-514674742946 · outbound

This paper cites Reinforcement Learning and Dynamic Programming Using Function Approximators.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Reinforcement Learning and Dynamic Programming Using Function Approximators

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.500116Z

Source-reported events for the cited work

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Observation 38387a55-f649-44cb-b148-3cd75afea5c5 · outbound

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Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 17

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Observation 18565ce6-2aeb-48bc-89e1-0c7b972ef5d1 · outbound

This paper cites Sutton, David A.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Sutton, David A

Reference 18

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Observation a39064e8-b6d7-4928-b4e0-4c18027758a3 · outbound

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Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 19

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Observation f869ce81-7077-4e59-afbb-1e32c262aa19 · outbound

This paper cites Riedmiller.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Riedmiller

Reference 20

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Observation 866a8033-9635-4e5d-be76-3d3867f939cf · outbound

This paper cites Multi-agent sys- tems by incremental gradient reinforcement learning.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Multi-agent sys- tems by incremental gradient reinforcement learning

Reference 21

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2cb127e6-adf7-4385-94ae-267bec94bbc4 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Playing Atari with Deep Reinforcement Learning

Reference 22

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Observation 08f6b8c8-0db3-4cf5-b2db-ef289ee903f8 · outbound

This paper cites Lillicrap, Jonathan J.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Lillicrap, Jonathan J

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.428964Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 77a671df-d574-42da-acc8-0da3f11eac35 · outbound

This paper cites Carlos Garcia-Monco, Elena Astigarraga, Ainara Gonzalez, and Jordan Grafman.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Carlos Garcia-Monco, Elena Astigarraga, Ainara Gonzalez, and Jordan Grafman

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.416072Z

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Observation c94113be-6588-4395-a970-8d932bb666f8 · outbound

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Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 25

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7a592191-4895-4e07-9653-3345cd79495f · outbound

This paper cites A softmin-based neural model for causal reason- ing.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking A softmin-based neural model for causal reason- ing

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.391194Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2f97b108-3462-4268-b618-7076a84ce547 · outbound

This paper cites Kingma and Jimmy Ba.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Kingma and Jimmy Ba

Reference 27

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Observation d9c3d5bc-d632-482e-8e23-541e7b44e4e7 · outbound

This paper cites Stewart, and Jimeng Sun.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Stewart, and Jimeng Sun

Reference 28

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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This paper cites Cooperative multi-agent control using deep reinforcement learning.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Cooperative multi-agent control using deep reinforcement learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.358980Z

Source-reported events for the cited work

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Observation f21a3529-4c2f-41fa-8f6c-339389ca3b12 · outbound

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Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 30

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Observation 55298849-d929-4f11-81ee-a652f369ab19 · outbound

This paper cites Causal inference in statistics: An overview.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Causal inference in statistics: An overview

Reference 31

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Observation 722d6eeb-fca0-4456-8d74-21ba7dac79cc · outbound

This paper cites Causal inference based on counterfactuals.

Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Causal inference based on counterfactuals

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.324920Z

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Observation 6299355d-f805-4d32-adda-feff392c1364 · outbound

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Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking Unresolved cited work

Reference 33

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Observation 76ac22de-a8df-42fb-b01b-0288f874fac2 · outbound

This paper cites Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications.

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

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Observation 13ee506f-08f8-4897-b7e9-6c960041cc10 · outbound

This paper cites WOLPERT and KAGAN TUMER.Optimal Payoff Functions for Members of Collectives , pages 355–369.

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:42:46.300364Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

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