Intelligence as Physical Computation

In this paper, we describe a model of physical computation that allows us to understand how embodied intelligent agents can simultaneously be considered to be objects operating under the laws of nature (or physics) and information processing devices. Using this type of analysis has two major advantages. First, it allows us to make concrete those issues relating to the relative merits of using analogue values or symbolic representations such as numbers: our analysis allows this longstanding point of contention in artificial intelligence to be transformed from a question of philosophy to one of physics. Second, it gives us a framework that should eventually allow us to produce design rules that will enable our artificially-intelligent (physical) agents to make better use of influences from the physical environment. As should be expected, for well-defined tasks, the results of this analysis are identical to Shannon’s information theory. However, for large, multi-functional systems with ill-defined roles, the new model provides a novel way of thinking about the complementarity of hardware and software.