The work described in this report is motivated by the desire to test the expressive possibilities of action language C+. The Causal Calculator (CCalc) is a system that answers queries about action domains described in a fragment of that language. The Zoo World and the Traffic World have been proposed by Erik Sandewall in his Logic Modelling Workshop—an environment for communicating axiomatizations of action domains of nontrivial size. -/- The Zoo World consists of several cages and the exterior, gates between (...) them, and animals of several species, including humans. Actions in this domain include moving within and between cages, opening and closing gates, and mounting and riding animals. The Traffic World includes vehicles moving continuously between road crossings subject to a number of restrictions, such as speed limits and keeping a fixed safety distance away from other vehicles on the road. We show how to represent the two domains in the input language of CCalc, and how to use CCalc to test these representations. (shrink)

In social interactions, it is common for individuals to possess different amounts of knowledge about a specific transaction, and those who are more knowledgeable might perform opportunistic behavior to others in their interest, which promotes their value but demotes others’ value. Such a typical social behavior is called opportunistic behavior. In this paper, we propose a formal account of opportunism based on the situation calculus. We first propose a model of opportunism that only considers a single action between two agents, (...) and then extend it to multiple actions and incorporate social context in the model. A simple example of selling a broken cup is used to illustrate our models. Through our models, we can have a thorough understanding of opportunism. (shrink)

A dynamic domain consists of a set of legal states and a transition function that maps states to states. AI formalisms for specifying dynamic domains have so far focused on describing the effects of actions, that is, the transition functions. In this paper we propose a notion of characteristic set of position systems for the purpose of describing legal states. A position system for a type of objects is a set of properties that are mutually exclusive, and that in each (...) state, every object of the type must satisfy exactly one of these properties called its position under the position system. A set of position systems, one for each type of objects in the domain, is characteristic if there is a one-to-one mapping between legal states and sets of objects’ positions under these position systems. These position systems are useful for reasoning about these dynamic systems including planning. In particular, we show that once we have characteristic sets of position systems for a dynamic domain, planning can be done by writing rules about when to move objects from one position to another. (shrink)