Deep Learning for Video Game Playing
Explore this paper's citation graph
- Type
- preprint
- Published
- 2017-08-25
- Cited by
- 237
- References
- 181
- Access
- Open access
- OpenAlex
- https://openalex.org/W2753316839
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:37941741
Keywords
Computer science, Video game, Context (archaeology), Artificial intelligence, Deep learning
References
- A general framework for parallel distributed processing
- Emergence in Games
- Recent Advances in Hierarchical Reinforcement Learning
- Reinforcement Learning for Robots Using Neural Networks
- Efficient Estimation of Word Representations in Vector Space
- Massively Parallel Methods for Deep Reinforcement Learning
- Neuroevolution in Games: State of the Art and Open Challenges
- Playing Atari with Deep Reinforcement Learning
- Language Understanding for Text-based Games using Deep Reinforcement Learning
- Machine learning in digital games: a survey
- The turing test track of the 2012 Mario AI Championship: Entries and evaluation
- Neurovisual Control in the Quake II Environment
- A Learning Algorithm for Continually Running Fully Recurrent Neural Networks
- Model-Free reinforcement learning with continuous action in practice
- A video game description language for model-based or interactive learning
- Computational intelligence in games
- Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990–2010)
- Evolving large-scale neural networks for vision-based reinforcement learning
- Evolutionary computation and games
- A Panorama of Artificial and Computational Intelligence in Games
Cited by
- ViZDoom: DRQN with Prioritized Experience Replay, Double-Q Learning, & Snapshot Ensembling
- PARAMETRIZED DEEP Q-NETWORKS LEARNING: PLAYING ONLINE BATTLE ARENA WITH DISCRETE-CONTINUOUS HYBRID ACTION SPACE
- The 2017 AIBIRDS Competition
- Automated Curriculum Learning by Rewarding Temporally Rare Events
- Adaptive CGF Commander Behavior Modeling Through HTN Guided Monte Carlo Tree Search
- Scaling Genetic Programming to Challenging Reinforcement Tasks through Emergent Modularity
- Procedural Level Generation Improves Generality of Deep Reinforcement Learning
- From ephemeral computing to deep bioinspired algorithms: New trends and applications
- Illuminating Generalization in Deep Reinforcement Learning through Procedural Level Generation
- Adding Neural Network Controllers to Behavior Trees without Destroying Performance Guarantees
- Computational optical tomography using 3-D deep convolutional neural networks
- Network-wide traffic signal control based on the discovery of critical nodes and deep reinforcement learning
- Generating Audio Using Recurrent Neural Networks
- Deep Recurrent Q-Learning vs Deep Q-Learning on a simple Partially Observable Markov Decision Process with Minecraft
- Reinforcement Learning for Extended Reality: Designing Self-Play Scenarios
- RLMViz: Interpreting Deep Reinforcement Learning Memory
- Deep neuroevolution of recurrent and discrete world models
- Learning a Behavioral Repertoire from Demonstrations
- Playing Atari with few neurons
- A Multifaceted Surrogate Model for Search-Based Procedural Content Generation
Related papers
- Analysis of multi-user video games in teacher training
- The Role of Structural Characteristics in Problem Video Game Playing: A Review
- Game 2.0 and beyond: an interaction design approach to digital game evolution
- Video game values: Human-computer interaction and games
- Intelligent adaptation of digital game-based learning
- A Proposed Method for Measuring Learning in Video Games
- User centered game design: evaluating massive multiplayer online role playing games for second language acquisition