Generalization in an autonomous agent

We present an extension of the previously defined model (1994). This model was introduced to govern an agent in a goal-programmed fashion in a previously unknown environment. The extension allows generalization in the input space, which reduces the memory requirements as well as the time requirements of the algorithm.<
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