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This paper presents a novel approach to the problem of action selection for an autonomous agent. An agent is viewed as a collection of competence modules. Action selection is modelled as an emergent property of an activation /inhibition dynamics among these modules. A concrete action selection algorithm is presented and a detailed account of the results is given. This algorithm combines characteristics of both traditional planners and reactive systems. It provides global parameters, which one can use to tune the action selection behavior along several criteria, such as goal orientedness versus situation orientedness, bias towards ongoing plans versus adaptivity, and sensitivity to goal conflicts and `thoughtfulness versus speed. 2 1 Introduction This paper addresses the following problem. Imagine an autonomous agent which has to achieve a number of global goals in a complex dynamic environment. An example could be a rover that has to explore Mars and collect samples of soi...
Pattie Maes (Sun,) studied this question.
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