A Comprehensive Review of Multi-Agent Reinforcement Learning in Video Games | Paper Citation Record

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

Reference 6

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

Reference 14

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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

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

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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:51:59.291440Z

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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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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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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:51:59.265704Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:51:59.257313Z

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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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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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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

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T10:51:58.683334Z

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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:51:59.240497Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:51:59.231992Z

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

Reference 32

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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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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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This paper cites Modular AI,.

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

Reference 35

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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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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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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

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This paper cites Actor-critic algorithms,.

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

Reference 39

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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

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This paper cites Proximal Policy Optimization Algorithms.

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

Reference 41

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This paper cites Shoham and K.

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

Reference 42

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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

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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

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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

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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

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This paper cites Strangers and friends,.

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

Reference 47

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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

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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

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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

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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

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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

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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

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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

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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

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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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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.

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.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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.

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.

Coverage vector

Reference resolution

Outbound references

Pith citing papers