Solving the Mountain Car Problem Using Genetic Algorithms
摘要
In this work, suitability of using Genetic Algorithms (GA) to solve the Mountain Car problem is investigated. Two variants, involving pure policies, as well as slightly extended mixed policies are considered. Experimental results, obtained with CPU-based parallel implementation are presented. They highlight challenges of the GA approach, related to high computational cost required for accurate evaluation of the fitness function.