A preference is not located anywhere in the agent's cognitive architecture, but it is rather a constraining of behavior which is in turn shaped by behavior. Based on this idea, a minimal model of behavioral preference is proposed. A simulated mobile agent is modeled with a plastic neurocontroller, which holds two separate high dimensional homeostatic boxes in the space of neural dynamics. An evolutionary algorithm is used for creating a link between the boxes and the performance of two different phototactic behaviors. After evolution, the agent's performance exhibits some important aspects of behavioral preferences such as durability and transitions. This article demonstrates (1) the logical consistency of the multi-causal view by producing a case study of its viability and providing insights into its dynamical basis and (2) how durability and transitions arise through the mutual constraining of internal and external dynamics in the flow of alternating high and low susceptibility to environmental variations. Implications for modeling autonomy are discussed.
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