Abstract:
The video game industry is an emerging market which continues to expand. From its early beginning, developers have focused mainly on sound and graphical applications, pay...Show MoreMetadata
Abstract:
The video game industry is an emerging market which continues to expand. From its early beginning, developers have focused mainly on sound and graphical applications, paying less attention to developing game bots or other kinds of nonplayer characters (NPCs). However, recent advances in artificial intelligence offer the possibility of developing game bots which are dynamically adjustable to several difficulty levels as well as variable game environments. Previous works reveal a lack of swarm intelligence approaches to develop these kinds of agents. Considering the potential of particle swarm optimization due to its emerging properties and self-adaptation to dynamic environments, further investigation into this field must be undertaken. This research focuses on developing a generic framework based on swarm intelligence, and in particular on ant colony optimization, such as it allows general implementation of real-time bots that work over dynamic game environments. The framework has been adapted to allow the implementation of intelligent agents for the classical game Ms. Pac-Man. These were trialed at the Ms. Pac-Man competitions held during the 2011 International Congress on Evolutionary Computation.
Published in: IEEE Transactions on Computational Intelligence and AI in Games ( Volume: 4, Issue: 4, December 2012)
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- IEEE Keywords
- Index Terms
- Video Games ,
- Ant Colony ,
- Artificial Intelligence ,
- Dynamic Environment ,
- Difficulty Level ,
- Particle Swarm Optimization ,
- Evolutionary Computation ,
- Ant Colony Optimization ,
- Swarm Intelligence ,
- Intelligence Approaches ,
- Game Environment ,
- Video Game Industry ,
- Optimal Parameters ,
- Gene Regulatory Networks ,
- End Of Process ,
- Set Of Rules ,
- Shortest Path ,
- Decision Rules ,
- Heuristic Algorithm ,
- Evolutionary Strategy ,
- Monte Carlo Tree Search ,
- Performance Of Agents ,
- Local Updates ,
- Solution Quality ,
- Game Conditions ,
- Artificial Intelligence Techniques ,
- Global Update ,
- Transition Rules ,
- Computational Intelligence ,
- Pheromone Trails
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Video Games ,
- Ant Colony ,
- Artificial Intelligence ,
- Dynamic Environment ,
- Difficulty Level ,
- Particle Swarm Optimization ,
- Evolutionary Computation ,
- Ant Colony Optimization ,
- Swarm Intelligence ,
- Intelligence Approaches ,
- Game Environment ,
- Video Game Industry ,
- Optimal Parameters ,
- Gene Regulatory Networks ,
- End Of Process ,
- Set Of Rules ,
- Shortest Path ,
- Decision Rules ,
- Heuristic Algorithm ,
- Evolutionary Strategy ,
- Monte Carlo Tree Search ,
- Performance Of Agents ,
- Local Updates ,
- Solution Quality ,
- Game Conditions ,
- Artificial Intelligence Techniques ,
- Global Update ,
- Transition Rules ,
- Computational Intelligence ,
- Pheromone Trails
- Author Keywords