mlsanityData to 7 Oct 2026

Deep Reinforcement Learning for General Video Game AI

arXiv 1806.02448 ↗First posted 6 Jun 2018cs.LG cs.AI cs.NEcited by 25

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Abstract (arXiv)

The General Video Game AI (GVGAI) competition and its associated software framework provides a way of benchmarking AI algorithms on a large number of games written in a domain-specific description language. While the competition has seen plenty of interest, it has so far focused on online planning, providing a forward model that allows the use of algorithms such as Monte Carlo Tree Search. In this paper, we describe how we interface GVGAI to the OpenAI Gym environment, a widely used way of connecting agents to reinforcement learning problems. Using this interface, we characterize how widely used implementations of several deep reinforcement learning algorithms fare on a number of GVGAI games. We further analyze the results to provide a first indication of the relative difficulty of these games relative to each other, and relative to those in the Arcade Learning Environment under similar conditions.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jun 2018.

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Citing papers per year: 2021: 8; 2022: 5; 2023: 4; 2024: 3; 2025: 4; 2026: 1.

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  1. 2025From System 1 to System 2: A Survey of Reasoning Large Language Modelscited by 319
  2. 2021Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Potcited by 97
  3. 2021Offline Meta-Reinforcement Learning with Online Self-Supervisioncited by 52
  4. 2022Machine Learning in Aerodynamic Shape Optimizationcited by 39
  5. 2021High-Accuracy Model-Based Reinforcement Learning, a Surveycited by 13
  6. 2022Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigationcited by 7
  7. 2021A Survey on Natural Language Video Localizationcited by 6
  8. 2021Physics-informed attention-based neural network for solving non-linear partial differential equationscited by 6
  9. 2023UniG3D: A Unified 3D Object Generation Datasetcited by 4
  10. 2025PuzzleJAX: A Benchmark for Reasoning and Learningcited by 4
  11. 2023Model-based Offline Policy Optimization with Adversarial Networkcited by 3
  12. 2021Pedestrian Collision Avoidance for Autonomous Vehicles at Unsignalized Intersection Using Deep Q-Networkcited by 2
13 more
  1. 2021Game Mechanic Alignment Theory and Discoverycited by 1
  2. 2022Deep Reinforcement Learning Using a Low-Dimensional Observation Filter for Visual Complex Video Game Playingcited by 1
  3. 2023Tree-Based Reconstructive Partitioning: A Novel Low-Data Level Generation Approachcited by 1
  4. 2025Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Gamescited by 1
  5. 2025Best Agent Identification for General Game Playingcited by 1
  6. 2026Spatial Reasoning in LLM Game Agents: Impact of Causal Context and Multi-Step Planningcited by 1
  7. 2021Planning from video game descriptionscited by 0
  8. 2022Reliable validation of Reinforcement Learning Benchmarkscited by 0
  9. 2022Machine Learning based Anomaly Detection for Smart Shirt: A Systematic Reviewcited by 0
  10. 2023All by Myself: Learning Individualized Competitive Behaviour with a Contrastive Reinforcement Learning optimizationcited by 0
  11. 2024MoMA: Model-based Mirror Ascent for Offline Reinforcement Learningcited by 0
  12. 2024Learning to Select Goals in Automated Planning with Deep-Q Learningcited by 0
  13. 2024A Safe Exploration Strategy for Model-free Task Adaptation in Safety-constrained Grid Environmentscited by 0