Behavior selection method for intelligent artificial creatures using the degree of consideration-based mechanism of thought

Artificial creatures need an intelligent behavior selection method to be used as an intermediate interface for natural interaction with users. For this purpose, the mechanisms of thought were proposed based on the probability and the degree of consideration. However, they were time-consuming when applying to an intelligent artificial creature with large numbers of wills, contexts and behaviors. Moreover, since the context-based evaluation only considers the behaviors short-listed by the will-based evaluation, some generated behaviors are inappropriate over the perceived contexts. To solve these problems, this paper proposes a novel behavior selection method for the intelligent artificial creatures using the degree of consideration-based mechanism of thought (DoC-MoT). The behaviors are short-listed by current dominant wills and perceived contexts and then they are globally evaluated by the fuzzy integral of the partial evaluation values of behaviors over artificial creature´s wills and external contexts, with respect to the fuzzy measure values representing its degrees of consideration. The effectiveness of the proposed behavior selection method is demonstrated by experiments carried out with a synthetic character “DD” in the 3D virtual environment. The results show that the generated behaviors were appropriate both to the current wills and the perceived contexts. Moreover, the computation time to select a behavior was decreased in the proposed method than the behavior selection methods using the probability-based MoT and DoC-MoT without the behavior short-listing.