General action languages, like e.g. the Situation Calculus, use full classical logic to represent knowledge of actions and their effects in dynamic domains. Description Logics, on the other hand, have been developed to represent static knowledge with the help of decidable subsets of first order logic. In this paper, we show how to use Description Logic as the basis for a decidable yet still exp...

In this paper, we show decidabil i ty of a rather expressive fragment of the situation calculus. We allow second order quantif ication over finite and inf inite sets of situations. We do not impose a domain closure assumption on actions; therefore, infinite and even uncountable domains are allowed. The decision procedure is based on automata accepting infinite trees.

Using the situation calculus as underlying formalism for specifying database updates as proposed by Raymond Reiter, a semantical notion of relevance of entries in tables to other entries is introduced. Also a semantical notion of relevant action is provided. Some properties of these semantical notions are investigated. In particular, they are compared with syntactical deenitions of relevance th...

Approaches to reasoning about knowledge in imperfect information games typically involve an exhaustive description of the game, the dynamics characterized by a tree and the incompleteness in knowledge by information sets. Such specifications depend on a modeler’s intuition, are tedious to draft and vague on where the knowledge comes from. Also, formalisms proposed so far are essentially proposi...

In this paper, we investigate bounded action theories in the situation calculus. A bounded action theory is one which entails that, in every situation, the number of object tuples in the extension of fluents is bounded by a given constant, although such extensions are in general different across the infinitely many situations. We argue that such theories are common in applications, either becau...

We propose a framework for robot programming which allows the seamless integration of explicit agent programming with decision-theoretic planning. Specifically, the DTGolog model allows one to partially specify a control program in a highlevel, logical language, but also provides an interpreter that— given a logical axiomatization of a domain—will determine the optimal completion of that progra...

Agents interacting with an incompletely known dynamic world need to be able to reason about the effects of their actions, and to gain further information about that world using sensors of some sort. Unfortunately, sensor information is inherently noisy, and in general serves only to increase the agent’s degree of confidence in various propositions. Building on a general logical theory of action...

In this paper we describe a framework for reasoning about temporal explanation problems , which is based on our previous work on model-based diagnosis of dynamic systems. We use an explicit representation of qualitative temporal information which provides a simpler and more natural representation than the situation calculus. We argue that a framework for reasoning about action should be able to...

In this paper we present an approach to representing and managing temporally-flexible behaviors in the Situation Calculus based on a model of time and concurrent situations. We define a new hybrid framework combining temporal constraint reasoning and reasoning about actions. We show that the Constraint Based Interval Planning approach can be imported into the Situation Calculus by defining a te...

The paper proposes a dialectic approach to exploit discrepancies of viewpoints for learning. The approach is illustrated with an elaborated example. A computational framework of a pedagogical agent capable of interacting with a learner for discussing different viewpoints in the same domain is outlined. The framework employs AI technologies, such as argumentation for defeasible reasoning, situat...