World Models, Action Selection, Embodied Concept Formation, and Conditioning

نویسنده

  • Terrence C. Stewart
چکیده

There are many computational models whose broad purpose is to allow an agent to learn via experience to perform effectively in a given environment. However, it is uncommon to see these models directly compared to each other, or to empirical data of real creatures adapting to their environments. Here, a comparison methodology is proposed involving various known results in classical and operant conditioning and concept formation. The project involves examining a broad selection of computational models in various environments, and also mixing and matching components from these different models.

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تاریخ انتشار 2004