Plan Recognition Using A Hypothesize and Revise Paradigm

Problem-Solving: Schmidt linearly ordered and unbounded in time. Plans are bounded, hierarchical, and nonlinearly ordered based on the logical connection between an enduring outcome of one action and the precondition of some subsequent action. Further, a plan is well-formed with reference to the planner's beliefs about the world rather than with respect to the actual state of the world. For these and similar reasons, we have argued that any process of plan recognition must use meta-knowledge about plans and the psychological constraints which define a well-formed plan. Knowledge of only the physical constraints on action does not provide sufficient information to recognize plans [8]. In this paper we present, by means of an example, those aspects of a plan recognition process that have been implemented in BELIEVER. The properties of this process have been motivated primarily by our desire to incorporate within this process certain psychological assumptions about characteristics of the human plan recognition process. The two major assumptions are that the human process is: (1) a general non-specialized process; and (2) is based on a hypothesize and revise strategy. The remainder of this paper is concerned with conveying the meaning of these labels. However, it will be useful to first explicate these ideas in an informal way. Because of interest in application or for methodological reasons, much of the recent work in AI has been concerned wxth the representation of expert knowledge within a relatively narrow domain. Chess, restaurants, flush toilets and particular electronic circuits are well-known examples of this approach. An expert's knowledge is, by definition, highly specialized and customized to a particular domain. This has led researchers to encode this knowledge in similarly specialized and customized forms which are often generically referred to as scripts [3). The use of script-like knowledge is an important aspect of the human information processing capability. A great deal of research has focused on the problem of how to generate a plan that satifies a given goal [2]. The problem of plan recognition is to take as input the sequence of actions performed by an actor and to identify the goal pursued by the actor and also to organize the action sequence in terms of a plan structure. This plan structure explicitly describes the goal-subgoal relations among its component units. Our concern with plan recognition has arisen from our research [4,5,6,7] in the development of a theory of how persons understand the …