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Paper Citation Record · LEDGER

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games

As of 9 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 0 inbound Pith citation observations for arXiv:2509.03682.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.03682 v1

Coverage vector

measured 84 of 84 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:51:56.870832Z

measured 84 of 84 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

84 of 84 outbound references displayed

  • verified exact7
  • verified fuzzy51
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e3dc315-d850-4fc2-820d-63b97b8903ad · outbound

This paper cites Video games remain America’s favorite pastime with more than 212 million Americans playing regularly,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Video games remain America’s favorite pastime with more than 212 million Americans playing regularly,

Reference 1

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no resolver link, observed 2026-08-05T10:51:55.329704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4959a035-d10b-4c98-aa5d-b0791b2980a5 · outbound

This paper cites GVR-4-68038-527-4,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games GVR-4-68038-527-4,

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1a43f34c-6445-4bb8-8323-dd4baa3d197d · outbound

This paper cites 2024 essential facts about the U.S. video game industry,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games 2024 essential facts about the U.S. video game industry,

Reference 3

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no resolver link, observed 2026-08-05T10:51:55.630270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.630270Z digest=sha256:69ea7beab314e8377e5f39ed917e4c160d689ec9fc214d6ef93a96d3d2edeb8b

Observation e821a649-c194-490d-9def-fdce0bc1d069 · outbound

This paper cites A machine for playing the game Nim,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games A machine for playing the game Nim,

Reference 4

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e781a5bc-48fa-45b4-a7dd-9281d36801f8 · outbound

This paper cites Understanding behavior trees,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Understanding behavior trees,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.636360Z digest=sha256:51eef8a05af47229fd3b88cfb07f6e52c37d339e5898bd1b0e291d1128d44f10

Observation f00c2ad3-b3e5-46ff-959d-47db68b687d8 · outbound

This paper cites an unresolved cited work.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Unresolved cited work

Reference 6

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unresolved
raw_fallback, observed 2026-08-05T10:51:59.342462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 876ef60d-4a86-4e90-a489-90a9932bb23f · outbound

This paper cites Using reinforcement learning to solve AI control problems,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Using reinforcement learning to solve AI control problems,

Reference 7

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raw_fallback, observed 2026-08-05T10:51:59.334265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.642482Z digest=sha256:93d6e5ff59522278130e7878796d65c68cdaec7a7a6ef77d64f86709910f3743

Observation afddbaf4-788d-4db8-a08b-a3c70c22b08d · outbound

This paper cites Connectionist reinforcement learning for intelligent unit micromanagement in StarCraft,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Connectionist reinforcement learning for intelligent unit micromanagement in StarCraft,

Reference 8

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raw_fallback, observed 2026-08-05T10:51:58.901174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.645303Z digest=sha256:db026f3e79b0d689842c44ccdc5e48acce7f29a42dcaa993aee108c6f3cc27e9

Observation 6b3fadd6-b650-4553-8264-1c341bba557f · outbound

This paper cites Go with the flow: Reinforcement learning in turn-based battle video games,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Go with the flow: Reinforcement learning in turn-based battle video games,

Reference 9

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raw_fallback, observed 2026-08-05T10:51:58.824503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.648388Z digest=sha256:111ed70c90bc65b3ef7cb9a2486d697b2c94d780ae64621e7f3f1494fe6b531c

Observation a134d1bf-93f5-4246-a593-2e5bd04fcecd · outbound

This paper cites A review of real -time strategy game AI,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games A review of real -time strategy game AI,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.651337Z digest=sha256:d224cd23843965e9792cb4282b4e018fcfad9619b42720e19e8e7d3a01f20ebc

Observation 6979e9ac-d099-467c-8fc0-7f161b3142e1 · outbound

This paper cites Human -level control th rough deep reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Human -level control th rough deep reinforcement learning,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.653948Z digest=sha256:aabfb6c726187135d1094babf6c7e75c7e63a5675021f2b359f5e5c5c2417bd0

Observation 24580eec-7934-4082-a9ce-fa355c2ea402 · outbound

This paper cites Playing FPS games with deep reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Playing FPS games with deep reinforcement learning,

Reference 12

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verified exact
doi, observed 2026-08-05T10:51:56.932869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.656727Z digest=sha256:745c619485844727aedd29f82da9a67af67799c196521a289fbb3e1e3f5f05e7

Observation 42a572b5-4734-4521-aef1-a8900594b2fc · outbound

This paper cites Deep reinforcement learning for navigation in AAA video games,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Deep reinforcement learning for navigation in AAA video games,

Reference 13

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verified exact
doi, observed 2026-08-05T10:51:56.923422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.659201Z digest=sha256:d4741b04b488e46a15a3df2f7bf06508e476f8326f6e2a167c3707cd17d02e20

Observation a98459be-091b-4357-911d-0ce793105003 · outbound

This paper cites an unresolved cited work.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 96f95acf-8b31-4010-9a16-ee6f6d426171 · outbound

This paper cites Mastering Atari, Go, chess and shogi by planning with a learned model,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Mastering Atari, Go, chess and shogi by planning with a learned model,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.300124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.664123Z digest=sha256:8587d8e78a8b3ca54f6446863c87e65d1537f169e5461c6a69f5d0f24f58bbaa

Observation 1d45322b-cde5-4023-b260-d87baeef19e5 · outbound

This paper cites Expert Human-Level Driving in Gran Turismo Sport Using Deep Reinforcement Learning with Image-based Representation.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Expert Human-Level Driving in Gran Turismo Sport Using Deep Reinforcement Learning with Image-based Representation

Reference 16

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local_arxiv, observed 2026-08-05T10:51:58.764087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.666721Z digest=sha256:96e16aef7a3317c80deb7443d86ddd7c3aee5fc85e583c9d3b6a68d9004836be

Observation dd447118-6f53-4b10-91bd-8367c159e9cf · outbound

This paper cites Super - human performance in Gran Turismo Sport using deep reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Super - human performance in Gran Turismo Sport using deep reinforcement learning,

Reference 17

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raw_fallback, observed 2026-08-05T10:51:59.291440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 818f4044-b49b-41ee-a22d-c328542eb0d3 · outbound

This paper cites Technical challenges of deploying reinforcement learning agents for game testing in AAA games,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Technical challenges of deploying reinforcement learning agents for game testing in AAA games,

Reference 18

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no resolver link, observed 2026-08-05T10:51:55.672432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 026565d2-c4ec-4647-bf27-6904c55f6a51 · outbound

This paper cites TD -Gammon, a self -teaching backgammon program, achieves master-level play,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games TD -Gammon, a self -teaching backgammon program, achieves master-level play,

Reference 19

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raw_fallback, observed 2026-08-05T10:51:59.282817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.675255Z digest=sha256:c328fd8efa94e45d869444e9bd38e107fa53848e2375e293fe9f81518cfd2571

Observation dfd2c73a-3f25-4751-b5b4-afd271f86c32 · outbound

This paper cites Mastering the game of Go with dee p neural networks and tree search,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Mastering the game of Go with dee p neural networks and tree search,

Reference 20

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raw_fallback, observed 2026-08-05T10:51:59.273906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.678691Z digest=sha256:9b22bb27709508cdcfa1a95985648a52484956acefbddd5e40ac9e37dfe631e2

Observation eb4bf056-0c5d-49fd-8ebe-748b7f4ed752 · outbound

This paper cites Mastering the game of Go without human knowledge,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Mastering the game of Go without human knowledge,

Reference 21

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raw_fallback, observed 2026-08-05T10:51:59.265704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.681980Z digest=sha256:abb3b44957f260c9b1473f081f0b2f54ed8c404719c67a143266bd5803752ff7

Observation 5b3b063c-cc52-466b-a99b-cd092439fefd · outbound

This paper cites A general reinforcement learning algorithm that masters chess, shogi, and Go through self -play,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games A general reinforcement learning algorithm that masters chess, shogi, and Go through self -play,

Reference 22

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raw_fallback, observed 2026-08-05T10:51:59.257313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.684847Z digest=sha256:8bd8c0771be897f6a90e06ad6fbd0eebee3a5c6358b0117e6b3a0df244a64927

Observation 3f05b17c-0595-4caf-ac47-7fb4af6f2566 · outbound

This paper cites Grandmaster level in StarCraft II using multi -agent reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Grandmaster level in StarCraft II using multi -agent reinforcement learning,

Reference 23

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raw_fallback, observed 2026-08-05T10:51:59.248530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.687801Z digest=sha256:51b0f2fcda33b70c6f870ae445c5becfbefd45b12f764f149426db79fdfc9140

Observation 3950dc73-be06-4b29-a8fc-56182e26c553 · outbound

This paper cites Dota 2 with Large Scale Deep Reinforcement Learning.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Dota 2 with Large Scale Deep Reinforcement Learning

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.691234Z digest=sha256:96fc86a45435c55c8a35715ed05cdd5f46e045b4db5664daadd4945f88ede874

Observation a5d431b0-ccab-4b04-a14e-1adfbdc53f0f · outbound

This paper cites A comprehensive survey of multiagent reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games A comprehensive survey of multiagent reinforcement learning,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.694691Z digest=sha256:03bdca1a53ad19d45ec5759ea4ad3f83c759d15846d9b28656b808fd35127c39

Observation 47c781be-8671-40e4-b91a-5110e6615ef6 · outbound

This paper cites Multi-agent reinforcement learning: A selective overview of theories and algorithms,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Multi-agent reinforcement learning: A selective overview of theories and algorithms,

Reference 26

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no resolver link, observed 2026-08-05T10:51:55.697893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.697893Z digest=sha256:985d01296aa66a9b9b3975c856225dc31f01965bd279487ea66668ad467ba2c2

Observation b6ef752c-d339-4902-b255-d84b16bc6bcc · outbound

This paper cites Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications,

Reference 27

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raw_fallback, observed 2026-08-05T10:51:59.240497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.701361Z digest=sha256:f92a410aa2c65b8c361eb85852469e48107f5e27ff653e59e988f3cc3f4b961f

Observation 582067ed-b6a6-48c8-ad1d-849f26540707 · outbound

This paper cites Multi-agent reinforcement learning: A review of challenges and applications,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Multi-agent reinforcement learning: A review of challenges and applications,

Reference 28

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raw_fallback, observed 2026-08-05T10:51:59.231992Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.704424Z digest=sha256:7005b41802fbc0f0fd44d43949f98b70cc29c5d194e35fe38571b0fe0e26477a

Observation fd6815f2-17ce-4627-9772-3248d1cb51fe · outbound

This paper cites Deep learning for video game playing,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Deep learning for video game playing,

Reference 29

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raw_fallback, observed 2026-08-05T10:51:59.223337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.707328Z digest=sha256:6827df2e80e2678056c33a6957193b1c3f02bcdcf1b544446bdc481a857cac55

Observation f5e1955c-1ac4-4787-9075-f8c746809685 · outbound

This paper cites Reinforcement learning in game industry—Review, prospects and challenges,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Reinforcement learning in game industry—Review, prospects and challenges,

Reference 31

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raw_fallback, observed 2026-08-05T10:51:59.215027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.717199Z digest=sha256:b4cc55bad6aae04f234528d8d978624fadd21034a455604ec2cf0a4f4c5d9411

Observation 320a8eb4-aeef-487f-8896-f017739cd99e · outbound

This paper cites Q-learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Q-learning,

Reference 32

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raw_fallback, observed 2026-08-05T10:51:59.206478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.720267Z digest=sha256:aeb3bb1c1d28a18ea22d55590162dc7e297a2fe4e2d3071f5a1fa216fef0236d

Observation 54ac3f35-93ab-4148-a257-9fe103b35e6d · outbound

This paper cites Policy gradient methods for reinforcement learning with function approximation,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Policy gradient methods for reinforcement learning with function approximation,

Reference 33

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raw_fallback, observed 2026-08-05T10:51:59.198183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.723483Z digest=sha256:23ad4dc07bffc16a8ffd7436e02876af09dbc31fb71867e0d43c903ada58e201

Observation 7c7cb991-9f4c-41e6-922b-a6089de2e0f6 · outbound

This paper cites Wooldridge, An Introduction to MultiAgent Systems , 2nd ed.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Wooldridge, An Introduction to MultiAgent Systems , 2nd ed

Reference 34

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raw_fallback, observed 2026-08-05T10:51:59.189913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.726589Z digest=sha256:380a25bcff18d4f49f5af7064278898c1f79db46c19bfb84008666763b2aa7d2

Observation 271dff9a-a9b8-4df8-9075-6fabca00527f · outbound

This paper cites Modular AI,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Modular AI,

Reference 35

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raw_fallback, observed 2026-08-05T10:51:59.181168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.729621Z digest=sha256:898f3d3177f9914c68e9b0503416f517b422d3e72c9095bb5d0da77b7c2ee0e3

Observation c5152184-8050-4e87-bb6f-292723c8c0d7 · outbound

This paper cites Long short -term memory,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Long short -term memory,

Reference 36

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raw_fallback, observed 2026-08-05T10:51:59.173091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.732768Z digest=sha256:a287399c2b5c955125bc1093c391fbf1e80b508642f2b4ca2b4f2ae9193f1710

Observation 240dde50-bde1-4897-9eae-01f42ef520d2 · outbound

This paper cites Deep recurrent Q -learning for partially observable MDPs,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Deep recurrent Q -learning for partially observable MDPs,

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.165087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.735651Z digest=sha256:cc2b68697939a87484959c4f8a95944b5d6db06026be6084aa4bfe782cc4c7a1

Observation 4185fa3e-7f39-4282-a920-c12c015e12ba · outbound

This paper cites Rainbow: Combining improvements in deep reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Rainbow: Combining improvements in deep reinforcement learning,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.156750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.739171Z digest=sha256:031e1e6d2c0916d9c9afe33bea4324ebd090eac40dfd80be6c39cd3db5c92fcb

Observation c0f59460-76f9-4e9d-ab05-a7c921e5764a · outbound

This paper cites Actor-critic algorithms,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Actor-critic algorithms,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.148062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.742552Z digest=sha256:9b81a57b33c7e68e5d10830542d78de64578c59f0b7d93dc7ff7286199ba409a

Observation d5e8b191-0414-4978-b80f-ae085f5f78d0 · outbound

This paper cites Continuous control with deep reinforcement learning.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Continuous control with deep reinforcement learning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.745729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.745729Z digest=sha256:fb6c7d4d0921c20a9b0effccb9b3651bf95f3dab9e1bb43eb482e95aae010693

Observation e00150c8-e970-4b99-a887-2b0c88d917c7 · outbound

This paper cites Proximal Policy Optimization Algorithms.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Proximal Policy Optimization Algorithms

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.749220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.749220Z digest=sha256:b12935a2cfe3ec4a2f8a0aeaf2409ef18612e5e59a8da805e5d417ab71e72b6e

Observation 3e8f741e-bf32-47b2-a334-188455af2349 · outbound

This paper cites Shoham and K.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Shoham and K

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.752466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.752466Z digest=sha256:733805318f4994b49e125a0a6606b12a1bb6d4b812e79a7f01ba018ce944ccac

Observation 5c2b3359-e747-4b8b-a572-6b9c88c8d7b2 · outbound

This paper cites Markov games as a framework for multi -agent reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Markov games as a framework for multi -agent reinforcement learning,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.138716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.755645Z digest=sha256:35413569a7db0c927466c3fa32a1f3cc476d08f0d444c4dbaea651f2a75ddafe

Observation 35e12052-9979-4661-b672-7cf6d0025978 · outbound

This paper cites Multiagent reinforcement learning: Theoretical framework and an algorithm,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Multiagent reinforcement learning: Theoretical framework and an algorithm,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.129920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.759034Z digest=sha256:5e1ad19a19c5ebf0b526d237559b549e216fc6fbae626dce6abc62da469cab7c

Observation 8902f8c8-294d-4d93-add5-e6776e5ee564 · outbound

This paper cites StarCraft II: A New Challenge for Reinforcement Learning.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games StarCraft II: A New Challenge for Reinforcement Learning

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.762086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.762086Z digest=sha256:a70ca1d824221ab79a7ec62b78810272a83d840a6d1bfb0e67a9f1f31fa9b847

Observation 5306b4e4-2b89-4618-b7ec-3ee871a64e7c · outbound

This paper cites The StarCraft Multi-Agent Challenge.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games The StarCraft Multi-Agent Challenge

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.765630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.765630Z digest=sha256:742158bbb9173b83627878d37596ee9558462f9e9d18bf81d0b5f3abb812ec05

Observation fc3e5dbe-5ac3-47c7-acaf-b65725809964 · outbound

This paper cites Strangers and friends,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Strangers and friends,

Reference 47

Resolution
metadata mismatch
raw_fallback, observed 2026-08-05T10:51:58.549403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.769658Z digest=sha256:b79b90f59cd1c0f09428407988318c981124b2762f60d80d505b7c8d8a58c624

Observation c9fddd94-74a2-4742-9f6a-bbdb43bbfc84 · outbound

This paper cites Hierarchical macro strategy model for MOBA game AI,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Hierarchical macro strategy model for MOBA game AI,

Reference 48

Resolution
verified exact
doi, observed 2026-08-05T10:51:56.901678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.773168Z digest=sha256:547e7c22651406e9cca92dd1c9dbee0ec7ec0c27b861a8e4c632b5856d4f5b2c

Observation b5b8daba-1c1d-48aa-9ce3-dcf29d763bbf · outbound

This paper cites Unifying temporal and structural credit assignment problems,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Unifying temporal and structural credit assignment problems,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.121596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.776471Z digest=sha256:d46c8b0773bc76faa1447e51f8fa723fe0232177ac023288597075a75cbe0823

Observation 082d136e-6184-4726-8ff8-1a16689a4d5b · outbound

This paper cites Multiagent systems: A survey from a machine learning perspective,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Multiagent systems: A survey from a machine learning perspective,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.112885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.780653Z digest=sha256:ba18ba254591c6b6430c56c98272211c772e305836f7513d82d89b5d615f71c1

Observation b444575f-b6e4-4039-a178-70caab8228eb · outbound

This paper cites Temporal difference learning and TD-Gammon,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Temporal difference learning and TD-Gammon,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.104463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.783776Z digest=sha256:0bff688669355cf11faed9737f860db943dc3fdca99c3488b05ad2e3fd0527a4

Observation 41f21917-81ed-417a-bbdb-01d46b2ab0d2 · outbound

This paper cites Creating pro-level AI for a real -time fighting game using deep reinfo rcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Creating pro-level AI for a real -time fighting game using deep reinfo rcement learning,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.095717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.786788Z digest=sha256:507632f2fcd06fc1fae49fd6965d24390dcd5cf76615f64b72c0ed640246733b

Observation eeed4ad4-a83b-4536-8958-ff13cd1f0f2c · outbound

This paper cites On the utility of learning about humans for human-AI coordination,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games On the utility of learning about humans for human-AI coordination,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.086582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.790699Z digest=sha256:b122efaa8224dcc3efcaa006309424745922889d61aef6e03f60c6d9874aa1b5

Observation c7166dbd-189a-4e17-a3c9-2a5a0656d18c · outbound

This paper cites IMPALA: Scalable distributed deep -RL with importance weighted actor -learner architectures,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games IMPALA: Scalable distributed deep -RL with importance weighted actor -learner architectures,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.077970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.797249Z digest=sha256:2851f77ca0ce6d522e3f8aee236ecba203ff14b013e75d2f0e30f22505ae9df7

Observation 553d7982-96b7-43f5-b711-3a185e24236b · outbound

This paper cites Distributed Prioritized Experience Replay.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Distributed Prioritized Experience Replay

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.800948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.800948Z digest=sha256:22ee8bfa5736068a15ab4f9949bd363b1a26d0389fe5fb5ed117977396913b29

Observation 5565a883-acd2-49b2-b9f5-2cbba4b28c59 · outbound

This paper cites Make a more engaging game w/ ML -Agents | Machine learning bots for game development | Reinforcement learning | Unity.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Make a more engaging game w/ ML -Agents | Machine learning bots for game development | Reinforcement learning | Unity

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.066823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.804667Z digest=sha256:4d54f7f50b06f835bc5bce27bb739d156c055811868a9d627d694733530b2dd9

Observation 054b1f78-c6ba-4b25-88e1-afee7779b33a · outbound

This paper cites Reinforcement Learning Agents for Ubisoft's Roller Champions.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Reinforcement Learning Agents for Ubisoft's Roller Champions

Reference 58

Resolution
verified exact
local_arxiv, observed 2026-08-05T10:51:57.252051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.807744Z digest=sha256:3816ded77d8afe2b895b7ed943a3cc3954092679fcece9edd3f11582400e32fc

Observation edc2a936-49b7-4ec0-979d-91ac9037ea7b · outbound

This paper cites MonoBehaviour.FixedUpd ate,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games MonoBehaviour.FixedUpd ate,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.058040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.811103Z digest=sha256:3f20446d74a02d920efabc5db3b7d1a097eeceb4d57fe4b6cc1765330fb1b42b

Observation df03024e-f9fc-4dd5-b893-03ac76d1ca89 · outbound

This paper cites On the verge of solving Rocket League using deep reinforcement learning and sim -to-sim transfer,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games On the verge of solving Rocket League using deep reinforcement learning and sim -to-sim transfer,

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.816478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.816478Z digest=sha256:c9b0406a045e77f1962168a83692c28c86b2dbd463f3fd317012a1922a01a175

Observation ae116335-4acc-41bd-a285-294bdef4c91d · outbound

This paper cites On the potential of Rocket League for driving team AI development,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games On the potential of Rocket League for driving team AI development,

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.833322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.833322Z digest=sha256:e8422ba4fdaf938fc789f3138d9b0cc5d9a11e0c808698cd72ac6ce9f32497c8

Observation 094bd1ae-03e0-4684-a67a-1824421a36c1 · outbound

This paper cites Lucy - SKG: Learning to play Rocket League efficiently using deep reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Lucy - SKG: Learning to play Rocket League efficiently using deep reinforcement learning,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.049561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:55.954533Z digest=sha256:48ca5fa4efe9e72da2717f38e091d4512f301a3165bfbd27de511fa53c10c3f9

Observation 9eb748f6-de58-4633-a415-2ce34a92f1e0 · outbound

This paper cites RLGym: Reinforcement learning in Rocket League,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games RLGym: Reinforcement learning in Rocket League,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.040763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.026084Z digest=sha256:3dd4dbf00295dd126087dda907bdbb43b97ce8ad9d188cd789e68151bd921b83

Observation 63952c26-80dc-4eae-b2dc-282e6a0bf633 · outbound

This paper cites Attention is all you need,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Attention is all you need,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.032720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.079281Z digest=sha256:640c0bb741e82d76f2827199edb4dea7492081738fab10a00db0e9fc9e1f8b75

Observation 5764aed7-f6c3-4485-8d58-538e0a4c93ee · outbound

This paper cites ViZDoom: A Doom-based AI research platform for visual reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games ViZDoom: A Doom-based AI research platform for visual reinforcement learning,

Reference 65

Resolution
metadata mismatch
raw_fallback, observed 2026-08-05T10:51:57.151109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.136791Z digest=sha256:d07bf53b57b75c9e2e7a628005abdbcf2da8dbc1a33b83b02acca95e2efe678a

Observation 19a7ccd9-0741-4dec-9c58-31546c90237f · outbound

This paper cites ViZDoom competitions: Playing Doom from pixels,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games ViZDoom competitions: Playing Doom from pixels,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.024639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.164586Z digest=sha256:7dcb7c658ee93aeeceb1be3aad52c5eeca484f25ba723fdbdbf198b39d75e111

Observation 5b694b81-2fec-4a90-aebe-9f8a40f199b9 · outbound

This paper cites Training agent for first -person shooter game with actor-critic curriculum learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Training agent for first -person shooter game with actor-critic curriculum learning,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.015956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.181626Z digest=sha256:278aa5c4c01523a16348d1ce652c5b32626befcd2bd676aeb27ee870fc223c83

Observation 248a5cbe-6cef-4ebd-8c7d-b93670f362d6 · outbound

This paper cites Asynchronous Methods for Deep Reinforcement Learning.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Asynchronous Methods for Deep Reinforcement Learning

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:56.247540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:56.247540Z digest=sha256:ba451b2fe4f662c5b19252155b5beb17b63dcd170c1ebfbff4e75d7d9a439a0f

Observation 49c5c432-aa1e-4b8b-b95f-9775516cd58f · outbound

This paper cites A Mi necraft-based simulated task environment for human-AI teaming,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games A Mi necraft-based simulated task environment for human-AI teaming,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:59.007758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.364463Z digest=sha256:3ceb826d375326e0b13327516728c17d9abb47b1167a5aa641282db003e6af45

Observation 2b02d60e-b1cd-4ceb-afe1-53f4c027e04f · outbound

This paper cites Minecraft as an experimental world for AI in robotics,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Minecraft as an experimental world for AI in robotics,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.999155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.478414Z digest=sha256:6c792d3f5c906e8e3407d1c799d78c3777f01ac268a5149e2e162bd8214ad636

Observation f5cf9446-1f41-4d73-a477-67dceeaac09b · outbound

This paper cites MineRL: A Large-Scale Dataset of Minecraft Demonstrations.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games MineRL: A Large-Scale Dataset of Minecraft Demonstrations

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:56.541888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:56.541888Z digest=sha256:0658b1d76d5b5db4aee20cd1b3465c933461a45620996cbb9415fa7d2547fd28

Observation db2aee90-238f-43b6-830a-971aa0f9aade · outbound

This paper cites The Malmo platform for artificial intelligence experimentation,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games The Malmo platform for artificial intelligence experimentation,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.990767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.639919Z digest=sha256:b3ddda2d4780acb91e369623cbd108fb3ed4c84db22a8bd202fb3a7b44002a1a

Observation 01c0b6c7-1d91-4fe5-a6dd-ee4af71c91fc · outbound

This paper cites The Malmo Collaborative AI Challenge - Microsoft Research,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games The Malmo Collaborative AI Challenge - Microsoft Research,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.982508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.749020Z digest=sha256:0b113ef4fc200637bccc3236cb52e4889a410aa4513dfd9bc26113aa8e5c2a8a

Observation 7cec5d4a-6e77-4cf2-902d-0dc251050807 · outbound

This paper cites HogRider: Champion agent of Microsoft Malmo collaborative AI challenge,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games HogRider: Champion agent of Microsoft Malmo collaborative AI challenge,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.973783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.839927Z digest=sha256:074beaa92e8c6eba6731cd59afdf10445d5678d7c3c5ef182c0f2afc7e1497b5

Observation 7a5f6f14-9b39-45ac-ac7d-23ee78b5bfe8 · outbound

This paper cites The Multi-Agent Reinforcement Learning in Malm\"O (MARL\"O) Competition.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games The Multi-Agent Reinforcement Learning in Malm\"O (MARL\"O) Competition

Reference 75

Resolution
verified exact
local_arxiv, observed 2026-08-05T10:51:56.968079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.843854Z digest=sha256:6adcb27e5a9bde6bad4d8d59a3c9eea7b28e3b52ffad3acbc078a6640560c956

Observation 196001a9-ce51-4e74-91b1-467615f4bc88 · outbound

This paper cites Human-level performance in 3D multiplayer games with population -based reinforcement learning,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Human-level performance in 3D multiplayer games with population -based reinforcement learning,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.965344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.846950Z digest=sha256:bcd3e5fb747acf7587c16cd51570a1a518dd3bedbc3d4f5a58c82f56bc5b559b

Observation c3f383b5-3c07-40f8-ae77-efa9cff09a02 · outbound

This paper cites The exploration - exploitation dilemma: A multidisciplinary framework,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games The exploration - exploitation dilemma: A multidisciplinary framework,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.956756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.849629Z digest=sha256:8827944f6df1ffc31ead8c94d3a2c46cbe588df9d3abc6c63f852d49016300ee

Observation f1e90818-862a-43aa-91f7-a7fc0841c3eb · outbound

This paper cites AlphaStar: Mastering the real -time strategy game StarCraft II,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games AlphaStar: Mastering the real -time strategy game StarCraft II,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.947906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.852283Z digest=sha256:f2de330da41d0cdbfa00a66e02f39994bddaf74ff22fe05394036664a5962965

Observation e5d1e515-c21c-4c48-9e89-6d7513a017fa · outbound

This paper cites Grid-wise control for multi-agent reinforcement learning in video game AI,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Grid-wise control for multi-agent reinforcement learning in video game AI,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.938545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.855374Z digest=sha256:de9f83b60b2f481fab196ad6d8efbb3fc45887fba8725759fc546c248d0a3342

Observation 9df9b4dd-c55f-429e-87de-0df495dda9e0 · outbound

This paper cites Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Games.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Games

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:56.858825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:56.858825Z digest=sha256:1cabd57e5760353cd0f4d3c5746f4f976592896778d27d4477f7d114986245d7

Observation eff00d2b-5e4c-4e9d-9932-004e4866158b · outbound

This paper cites Ye, et al., Towards playing full MOBA games with deep reinforcement learning, vol.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Ye, et al., Towards playing full MOBA games with deep reinforcement learning, vol

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.928821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.862563Z digest=sha256:365658c999c93ddb54bb337221fdb6fb221ff37a3a161b532c28801b766aa101

Observation 80e174de-bc66-4a8d-82ef-3ad4065713ba · outbound

This paper cites A recommender system for hero line-ups in MOBA games,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games A recommender system for hero line-ups in MOBA games,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.920163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.865286Z digest=sha256:11834a4e9651866df19de4d5fc5e96f4539d9576ebf173d70b5e43d21390541d

Observation 7cf67657-3f80-4647-87b7-b2cd5872e63d · outbound

This paper cites The Art of Drafting: A Team-Oriented Hero Recommendation System for Multiplayer Online Battle Arena Games.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games The Art of Drafting: A Team-Oriented Hero Recommendation System for Multiplayer Online Battle Arena Games

Reference 83

Resolution
verified exact
local_arxiv, observed 2026-08-05T10:51:56.945969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.867925Z digest=sha256:ac399515ab3ec2056795f8acee078bfa33acf14752de3d077645222ac235bcb4

Observation 36fbe881-e683-4567-876b-e6edf724df5f · outbound

This paper cites Acting with style: Towards designer-centred reinforcement learning for the video games industry,.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Acting with style: Towards designer-centred reinforcement learning for the video games industry,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:51:58.911380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T10:51:56.870832Z digest=sha256:e1ca123f2ad7c775d02391fa8f84a3aa4aa80e35e04e0eb37a09ef73b31e367d

Observation 418233a4-e818-4275-857a-7746f2530211 · outbound

This paper cites A Survey of Deep Reinforcement Learning in Video Games.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games A Survey of Deep Reinforcement Learning in Video Games

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.714335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.714335Z digest=sha256:adecf231d7875a146d6b8584f99ae081d8fb5d97383d452c72e80daebe0b37f6

Observation b57a8584-71b8-4c2a-97c9-eca9497c757d · outbound

This paper cites Available: https://www.grandviewresearch.com/ industry-analysis/video-game-market.

A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games Available: https://www.grandviewresearch.com/ industry-analysis/video-game-market

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-05T10:51:55.545689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:51:55.545689Z digest=sha256:c323058ce427c41cbdd5f167749b45d3e38c979ae06b967bbd56e4e920ec0914

Pith citing papers

No inbound Pith citation observations are available.