Tree Depth Influence in Genetic Programming for Generation of Competitive Agents for RTS Games.
Pablo García-SánchezAntonio Fernández-AresAntonio Miguel MoraPedro Ángel Castillo ValdiviesoJesús GonzálezJuan Julián Merelo GuervósPublished in: EvoApplications (2014)
Keyphrases
- genetic programming
- fitness evaluation
- learning agents
- game theoretic
- minority game
- multi agent systems
- nash equilibria
- fitness function
- evolutionary computation
- multi agent
- opponent modeling
- coalitional games
- multiagent systems
- multi agent decision making
- bounded rationality
- intelligent agents
- multiagent learning
- autonomous agents
- game theory
- evolutionary algorithm
- cooperative
- multiple agents
- symbolic regression
- financial forecasting
- gene expression programming
- resource allocation
- stochastic games
- solution concepts
- single agent
- regression problems
- game playing
- cooperative game
- game players
- depth map
- tree structure
- imperfect information
- educational games
- genetic algorithm
- reinforcement learning agents
- coalition formation
- dynamic environments
- personality traits
- artificial agents
- software agents
- rational agents
- game tree
- incomplete information
- search algorithm
- online game
- grammar guided genetic programming
- decision making
- cooperative games
- two player games
- nash equilibrium
- mixed strategy
- agent architecture
- depth information
- social welfare
- index structure
- mobile agents
- agent technology
- human players
- data structure
- reinforcement learning
- neural network
- coalition structures
- transferable utility
- mechanism design