We introduce a novel multi agent patrolling algorithm inspired by the behavior of gas filled balloons. Very low capability ant-like agents are considered with the task of patrolli...
Traditional approaches to combining classifiers attempt to improve classification accuracy at the cost of increased processing. They may be viewed as providing an accuracy-speed tr...
Kumar Chellapilla, Michael Shilman, Patrice Simard
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Many agent problems in a grid world have a restricted sensory information and motor actions. The environmental conditions need dynamic processing of internal memory. In this paper...
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...