Reinforcement learning (RL) is a method which provides true learning capabilities regarding situation-based actions. RL-systems explore and self-optimise actions for situations in a defined environment. This paper describes the research of a driver (assistance) system based on pure reinforcement learning in the framework of an autonomous vehicle. The target of this research is to determine to what extent RL-based systems serve as an enhancement or even an alternative to classical concepts of autonomous intelligent vehicles such as modelling or neural nets.


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    Title :

    Optimising situation-based behaviour of autonomous vehicles


    Contributors:
    Krodel, M. (author) / Kuhnert, K.-D. (author)


    Publication date :

    2004-01-01


    Size :

    809984 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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