The Epsilon State

Terminology and deenitions are proposed for the application of systems concepts to Adaptive Behavior research. The deenition of a system can be applied to agents and environments in several ambiguous ways. For this reason, a distinction is introduced between a mechanistic perspective and a functional perspective. For both perspectives a methodology is proposed for estimating the number of states of an agent, yielding the Mechanistic Epsilon State Count and the Functional Epsilon State Count, respectively. In addition , a similar means is proposed for counting the number of states required to perform a particular task in an environment: the Task Epsilon State Count. Importantly, the methodology explicitly looks for and reports the relation between the number of states and their eeect on performance. This methodology provides a uniform language to describe and compare diierent agents and environments , and for this reason it may aaord valuable comparisons between diierent Adaptive Behavior studies.