To make artificial creatures interact with their environment like living creatures, a proper behavior selection method is needed. For this purpose, there has been research on the behavior selection method for artificial creatures mimicking the mechanism of thought of human beings. Much of this research is based on probabilistic knowledge links between input (assumed fact) and target (behavior) symbols for reasoning, which is the probability-based mechanism of thought. However, real intelligent creatures including human beings select a behavior based on the multi-criteria decision making process considering the degree of consideration (DoC) for each of input symbols, such as will and context symbols, in their memory. In this paper, the DoC-based mechanism of thought is proposed and applied to the behavior selection of artificial creatures. The knowledge links between input and behavior symbols are represented by partial evaluation values of behaviors over each of input symbols, and the degree of consideration for input symbols is represented by fuzzy measure. The proposed method selects a behavior through global evaluation by fuzzy integral, as a multi-criteria decision making process, of knowledge link strengths with respect to DoC values. The effectiveness of proposed behavior selection method is demonstrated by simulations carried out with a synthetic character "Rity" in the 3-D virtual environment.