Much of commonsense knowledge about the real world is in the form of procedures or sequences of actions for achieving particular goals. In this paper, a formalism is presented for representing such knowledge using the notion of process.
In this paper we present a theory of referring. This theory is presented within the framework of a general theory of speech acts and rationality advanced by Cohen and Levesque.
The approach proposed by Carnap for the development of logical bases for probability theory is investigated by using formal structures that are based on epistemic logics.
In order to plan operations where knowledge of significant elements is imprecise and uncertain, a means of characterizing the situation in terms of the various factors that may influence those operations must be provided.
The importance of plan inference in models of conversation has been widely noted in the com-putational-linguistics literature, and its incorporation in question-answering systems has enabled a range of cooperative behaviors.
This paper describes a new technique for use in the automatic production of digital terrain models from stereo pairs of aerial images. This technique employs a coarse-to-fine hierarchical control structure both for global constraint propagation and for efficiency.
Most AI domain representations have been based on state-oriented world models. In this paper we present an event-based model that focuses on domain events (both atomic and nonatomic) and on the causal and temporal relationships among them.
Problems in commonsense and robot planning are approached by methods adapted from program synthesis research; planning is regarded as an application of automated deduction.
