Recently Lakemeyer and Levesque proposed the logic, 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 knowledge bases and queries, including epistemic ones, query evaluation requires first-order reasoning only. We also provide a simple semantic definition of progressing a knowledge base. For a particular class of knowledge bases, adapted from earlier results by Lin and Reiter, we show that progression is first-order representable and easy to compute. 1

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Agents interacting with an incompletely known world need to be able to reason about the effects of their actions, and to gain further information about that world they need to use sensors of some sort. Unfortunately, both the effects of actions and the information returned from sensors are subject to error. To cope with such uncertainties, the agent can maintain probabilistic beliefs about the state of the world. With probabilistic beliefs the agent will be able to quantify the likelihood of the various outcomes of its actions and is better able to utilize the information gathered from its error-prone actions and sensors. In this paper, we present a model in which we can reason about an agent's probabilistic degrees of belief and the manner in which these beliefs change as various actions are executed. We build on a general logical theory of action developed by Reiter and others, formalized in the situation calculus. We propose a simple axiomatization that captures an agent's state of ...

Acquiring information about its environment by sensing is a crucial ability of autonomous robots. Based on the established solution to the Frame Problem of the Fluent Calculus, we present a new, unifying formalism for representing and reasoning about sensing actions, knowledge preconditions, conditional actions, non-knowledge, and about what goals a robot can possibly achieve. In A. Cohn and F. Giunchiglia and B. Selman, editors, Proc. of the International Conference on Principles of Knowledge Representation and Reasoning, pages 109-120, Breckenridge, CO, 2000. Morgan Kaufmann 1 INTRODUCTION Intelligent, autonomous robots choose most of their actions conditioned on the state of their environment. They are equipped with sensors for the purpose of acquiring information about the external world. Robots that perform reasoning about their goals and actions thus need an explicit representation of what they know of a state and how sensing aects their knowledge [ Moore, 1985 ] . F...

The ability to reason about action and change has long been considered a necessary component for any intelligent system. Many proposals have been offered in the past to deal with this problem. In this paper, we offer a new approach to belief change associated with performing actions that addresses some of the shortcomings of these approaches. In particular, our approach is based on a well-developed theory of action in the situation calculus extended to deal with belief. Moreover, our account handles nested belief, belief introspection, mistaken belief, and handles belief revision and belief update together with iterated belief change. 1

We consider a class of knowledge-based programs with sense actions. These programs refer explicitly to an agent's knowledge, and are designed to...

GOLOG is a high-level programming language for the specification of complex actions. It combines the situation calculus with control structures known from conventional programming languages. Given a suitable axiomatization of what the world is like initially and how the primitive actions change the world, the GOLOG interpreter derives for each program a corresponding linear sequence of legally executable primitive actions, if one exists. Despite its expressive power, GOLOG's applicability is severely limited because the derivation of a linear sequence of actions requires that the outcome of each action is known beforehand. Sensing actions do not meet this requirement since their outcome can only be determined by executing them and not by reasoning about them. In this paper we extend GOLOG by incorporating sensing actions. Instead of producing a linear sequence of actions, the new interpreter yields a tree of actions. The idea is that a particular path in the tree represents a legal execution of primitive actions conditioned on the possible outcome of sensing actions along the way.

The focus of current research in cognitive robotics is both on the realization of systems based on known formal settings and on the extension of previous formal approaches to account for features that play a significant role for autonomous robots, but have not yet received an adequate treatment. In this paper we adopt a formal framework derived from Propositional Dynamic Logics by exploiting their formal correspondence with Description Logics, and present an extension of such a framework obtained by introducing both concurrency on primitive actions and autoepistemic operators for explicitly representing the robot’s epistemic state. We show that the resulting formal setting allows for the representation of actions with contextdependent effects, sensing actions, and concurrent actions, and address both the presence of exogenous events and the characterization of the notion of executable plan in such a complex setting. Moreover, we present an implementation of this framework in a system which is capable of generating plans that are actually executed on mobile robots, and illustrate the experimentation of such a system in the design and implementation of soccer players for the 1999 Robocup competition.

The Cognitive Agents Specification Language (CASL) is a framework for specifying multiagent systems. It has a mix of declarative and procedural components to facilitate the specification and verification of complex multiagent systems. In this paper, we describe CASL and a verification environment (CASLve) for it based on the PVS verification system. We give an example of a multiagent meeting schedulerapplication specified with CASL. To illustrate the verification system, we discussa proof we carried out in it, namely, that all bounded-loop CASL specifications terminate. Categories and Subject Descriptors I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence—multiagent systems; D.2.1 [Software Engineering]:

. In this paper, we describe a framework for specifying communicative multi-agent systems, using a theory of action based on the situation calculus to describe the effects of actions on the world and on the mental states of agents; and the concurrent, logic programming language ConGolog to specify the actions performed by each agent. Since ConGolog has a well-defined semantics, the specifications can be used to reason about the behavior of individual agents and the system as a whole. We extend the work presented in [7] to allow the specifications to mention agents' goals explicitly. The framework presented here allows the behavior of different agents to be specified at different levels of abstraction, using a rich set of programming language constructs. As an example, we specify a meeting scheduler multi-agent system. 1 Introduction Many agent theorists (some examples are [1, 14, 19]) follow a similar methodology. They present a framework for representing the mental states ...