All effective agents are context-sensitive. This is true for biological agents, and it must also be true for artificial agents if they are to succeed. Context-mediated behavior (CMB) is one approach to endowing artificial agents with context-sensitive, context- appropriate behavior. It relies on explicitly representing contexts—important classes of situations—as contextual schemas and associating with them all the relevant knowledge about that context. The agent can then use these c-schemas to assess its context and their knowledge to behave appropriately. In this paper, we provide an overview of CMB, review the past work on it, discuss what we have learned from more than twenty years of working on the problem, and describe where we are and where we are going with CMB.
Roy M. Turner, Context-mediated behavior. Modeling and Using Context, forthcoming in 2017.