Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
We present a domain independent off-line adaptation technique called Stochastic Plan Optimization for finding and improving plans in real-time strategy games. Our method is based ...
In this work we explore how the complexity of a problem domain affects the performance of evolutionary search using a performance-based restart policy. Previous research indicates...
The problem of finding the binomial population with the highest success probability is considered when the number of binomial populations is large. A new rigorous indifference zo...
Abstract- Interactive combat games are useful as testbeds for learning systems employing evolutionary computation. Of particular value are games that can be modified to accommodate...