Abstract. We develop an approach in which we model communication protocols via commitment machines. Commitment machines supply a content to protocol states and actions in terms of the social commitments of the participants. The content can be reasoned about by the agents thereby enabling flexible execution of the given protocol. We provide reasoning rules to capture the evolution of commitments through the agents ’ actions. Because of its representation of content and its operational rules, a commitment machine effectively encodes a systematically enhanced version of the original protocol, which allows the original sequences of actions as well as other legal moves to accommodate exceptions and opportunities. We show how a commitment machine can be compiled into a finite state machine for efficient execution, and prove soundness and completeness of our compilation procedure. 1

The goal of this paper is to extend classical logic with a generalized notion of inductive definition supporting positive and negative induction, to investigate the properties of this logic, its relationships to other logics in the area of non-monotonic reasoning, logic programming and deductive databases, and to show its application for knowledge representation by giving a typology of definitional knowledge.

A knowledge representation formalism...

In this paper we present a language to reason about actions in a probabilistic setting and compare our work with earlier work by Pearl and (also briefly with) representations used in probabilistic planning. The main feature of our language is its use of static and dynamic causal laws, and use of unknown (or background) variables -- whose values are determined by factors beyond our model -- in incorporating probabilities. We also incorporate probabilities into reasoning with narratives. 1

An additive fluent is a fluent with numerical values such that the effect of several concurrently executed actions on it can be computed by adding the effects of the individual actions. We propose a method for describing effects of actions on additive fluents in the declarative language C+. An implementation of this language, called the Causal Calculator, can be used for the automation of examples of commonsense reasoning involving additive fluents.

How can an intelligent agent update her knowledge base about an action domain, relative to some conditions (possibly obtained from earlier observations)? We study this question in a formal framework for reasoning about actions and change, in which the meaning of an action domain description can be represented by a directed graph whose nodes correspond to states and whose edges correspond to action occurrences. We define the update of an action domain description in this framework, and show among other results that a solution to this problem can be obtained by a divide-and-conquer approach in some cases. We also introduce methods to compute a solution and an approximate solution to this problem, and analyze the computational complexity of these problems. Finally, we discuss techniques to improve the quality of solutions. 1

Abstract. Wire routing is the problem of determining the physical locations of all the wires interconnecting the circuit components on a chip. Since the wires cannot intersect with each other, they are competing for limited spaces, thus making routing a difficult combinatorial optimization problem. We present a new approach to wire routing that uses action languages and satisfiability planning. Its idea is to think of each path as the trajectory of a robot, and to understand a routing problem as the problem of planning the actions of several robots whose paths are required to be disjoint. The new method differs from the algorithms implemented in the existing routing systems in that it always correctly determines whether a given problem is solvable, and it produces a solution whenever one exists.

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In this work we address the problem of elaborating domain descriptions (alias action theories), in particular those that are expressed in dynamic logic. We define a general method based on contraction of formulas in a version of propositional dynamic logic with an incorporated solution to the frame problem. We present the semantics of our theory change and define syntactical operators for contracting a domain description. We establish

This paper presents a solution in a first-order monotonic logic to a simplified version of the Surprise Birthday Present Problem, a challenge problem for the formal commonsense reasoning community. The problem concerns two siblings who wish to surprise their sister with a present for her birthday: the aim is to construct a theory that will support the desired inferences, not allow undesired inferences, and be sufficiently elaboration tolerant to support reasoning about problem variations. The theory presented in this paper includes the development of a possible-worlds analysis of the concept of surprise, and an extension to previous work on multiple-agent planning to handle joint planning and actions. We show that this theory can solve the original SBP as well as many of its variants.