Different animals employ different strategies for sampling sensory data. In animals that can see, differences in sampling strategy manifest themselves as differences in field of view and in spatially variant sampling (so-called foveal vision). In analyzing adaptive behavior in animals, or attempting to design autonomous robots, mechanisms for exploring variations in sensory sampling strategy will be required. This article describes our work exploring a minimal system for investigating the effects of variations in patterns of sensory sampling. We have reimplemented Wilson's animat (Wilson, 1985b) and then experimented with altering its sensory sampling pattern (i.e., its sensory field). Empirical results are presented which demonstrate that alterations in the sensory field pattern can have a significant effect on the animat's observable behavior. Analysis of our results involves characterizing the interaction between the animat's sensory field and the environment within which the animat resides. We found that the animat's observed behavior can, at least in part, be explained by the animat cautiously moving in a manner that attempts to maximize the generation of new information from the environment over time. We demonstrate that similar explanations can be offered for behavioral patterns in real animals. The article concludes with a discussion of the generality of the results and reflections on the prospects for further work.
- Wilson's animat
- sensory sampling
- agent-environment interaction
- classifier system