Q-learning with heuristic exploration in Simulated Car Racing
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منابع مشابه
Generalization of TORCS car racing controllers with artificial neural networks and linear regression analysis
Designing controllers for simulated cars is a challenging task because there are numerous sensor inputs and a lot of actuators to be controlled. Although it is possible to use domain-expert knowledge on the car racing, it is not trivial to represent the knowledge into controllers and tune the parameters for them. Therefore, it is natural to adopt machine learning approach into the knowledge-ori...
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Videogame-based competitions are receiving a lot of interest in the last few years, as they provide an ideal framework to apply soft computing techniques. One the most popular competitions is the Simulated Car Racing Competition and thanks to the realism implemented by recent car simulators, it provides a test framework for the application of autonomous driving techniques. This work presents th...
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TORCS car racing bots have improved significantly in the last years. We show that accurate curvature information for the upcoming corners enables offline learning a near-optimal driving style that consistently beats an expert human player (and the fastest currently known bots). Generalization to other tracks often, but not always succeeds, so that the method is extended by an online error corre...
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تاریخ انتشار 2013