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...

To design protocols among computational agents, we have adopted Searle and Vanderveken model of speech acts because this model is a rich theory which can give important properties of protocols that we can formalize properly. To achieve this, we are working on an adequate formalism (the situation calculus) for representing this model in the context of multiagent systems.

Recently the general Game Description Language (GDL) has been extended so as to cover arbitrary games with incomplete/imperfect information. Learning—without human intervention—to play such games poses a reasoning challenge for general game-playing systems that is much more intricate than in case of complete information games. Action formalisms like the Situation Calculus have been developed fo...

In this paper we investigate situation calculus action theories extended with ontologies, expressed as description logics TBoxes that act as state constraints. We show that this combination, while natural and desirable, is particularly problematic: it leads to undecidability of the simplest form of reasoning, namely satisfiability, even for the simplest kinds of description logics and the simpl...

Our focus in this paper is on natural exoge-nous actions (Pinto 23]), namely those which occur in response to known laws of physics, like a ball bouncing at times determined by Newtonian equations of motion. The property of such actions that we wish to capture is that they must occur at their predicted times, provided no earlier actions (natural or agent initiated) prevent them from occurring. ...

We define the robustness of a sequential plan as the probability that it will execute successfully despite uncertainty in the execution environment. We consider a rich notion of uncertainty over continuous domains that includes stochastic action effects, and changes to state variables due to unpredictable exogenous events. Given a characterization of this uncertainty in terms of probability dis...

Recently Lakemeyer and Levesque proposed the logic AOL, which amalgamates both the situation calculus and Levesque’s logic of only knowing. While very expressive the practical relevance of the formalism is unclear because it heavily relies on second-order logic. In this paper we demonstrate that the picture is not as bleak as it may seem. In particular, we show that for large classes of AOL kno...