BookDOI
Computational intelligence in games
Janusz Kacprzyk,Norio Baba,Lakhmi C. Jain +2 more
- pp 161-161
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TLDR
A neural network is evolved to play checkers without human expertise using model-based reinforcement learning and fuzzy rule-based strategy for a market selection game.Abstract:
Introduction to computational intelligence paradigms.- Evolving a neural network to play checkers without human expertise.- Retrograde analysis of patterns versus metaprogramming.- Learning to evaluate Go positions via temporal difference methods.- Model-based reinforcement learning for evolving soccer strategies.- Fuzzy rule-based strategy for a market selection game.-read more
Citations
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Journal ArticleDOI
Search-Based Procedural Content Generation: A Taxonomy and Survey
TL;DR: This article contains a survey of all published papers known to the authors in which game content is generated through search or optimisation, and ends with an overview of important open research problems.
Journal ArticleDOI
A Panorama of Artificial and Computational Intelligence in Games
TL;DR: This paper attempts to give a high-level overview of the field of artificial and computational intelligence in games, with particular reference to how the different core research areas within this field inform and interact with each other, both actually and potentially.
Journal ArticleDOI
Deep Learning for Video Game Playing
TL;DR: The unique requirements that different game genres pose to a deep learning system are analyzed and important open challenges in the context of applying these machine learning methods to video games, such as general game playing, dealing with extremely large decision spaces and sparse rewards are highlighted.
Journal ArticleDOI
Coadaptive Brain–Machine Interface via Reinforcement Learning
TL;DR: This paper introduces and demonstrates a novel brain-machine interface (BMI) architecture based on the concepts of reinforcement learning (RL), coadaptation, and shaping, and quantifies BMI performance in closed-loop brain control over six to ten days for three rats as a function of increasing task difficulty.
Journal ArticleDOI
Neuroevolution in Games: State of the Art and Open Challenges
Sebastian Risi,Julian Togelius +1 more
TL;DR: This paper surveys research on applying neuroevolution to games along five different axes, which are the role NE is chosen to play in a game, the different types of neural networks used, the way these networks are evolved, how the fitness is determined and what type of input the network receives.