We present the basic framework of a logic of actions and plans defined in terms of modal logic combined with a notion of dependence. The latter is used as a weak causal connection between actions and literals. In this paper we focus on the frame problem and demonstrate how it can be solved in our framework in a simple and monotonic way. We give the semantics, and associate an axiomatics and a decision procedure to it. The decision procedure is based on a sound and complete tableau method with single step rules to treat dependence. We show how it can be used to generate plans. Our solution is formally assessed by a translation of Gelfond and Lifschitz' logic A. We briefly sketch the second part of the paper, showing how we can go beyond A by some examples involving nondeterminism and ramifications.

Abstract. In this paper we describe a language for reasoning about actions that can be used for modelling and for programming rational agents. We propose a modal approach for reasoning about dynamic domains in a logic programming setting. Agent behavior is specified by means of complex actions which are defined using modal inclusion axioms. The language is able to handle knowledge producing actions as well as actions which remove information. The problem of reasoning about complex actions with incomplete knowledge is tackled and the temporal projection and planning problems is addressed; more specifically, a goal directed proof procedure is defined, which allows agents to reason about complex actions and to generate conditional plans. We give a non-monotonic solution for the frame problem by making use of persistency assumptions in the context of an abductive characterization. The language has been used for implementing an adaptive web-based system.

The paper presents a logic for action theory based on a modal language, where modalities represent actions. Persistency is achieved by using a nonmonotonic formalism which maximizes persisitency assumptions. The problem of ramification is tackled by introducing a modal causality operator which is used to represent causal rules. Assumptions on the value of fluents in the initial state allow to reason with incomplete initial states and to do postdiction. The action theory can also deal with non-minimal change and nondeterministic actions. 1 Introduction Reasoning about action and change is one of the main topics which must be addressed in building intelligent agents. Among the various approaches to reasoning about actions, one of the most popular is still the situation calculus. The situation calculus represents states of the world (situations) as sequences of actions, and fluents are relations whose truth values vary from state to state. The situation calculus is formulated in ...

. In this paper we present an approach for dealing with concurrent actions based on a modal action theory. It is an extension of the approach presented in a previous paper in which modalities are used to represent actions, and causal rules are introduced to address the ramification problem. An abductive semantics is adopted to deal with persistency. In this paper we extend the action language by introducing two different modalities for dealing with "open" and "closed" actions. Moreover, we show that causal rules play a crucial role for modelling concurrent actions. 1 Introduction In this paper we present an approach for dealing with concurrent actions based on a modal action theory developed in [8] (and, for the more restricted Logic Programming case, in [2]), in which actions are represented as modalities. The adoption of a modal approach is common with other proposals for modeling actions [6, 5, 21], which are based on modal logics and on Dynamic Logic [10]. In fact, modal logic al...

In this paper we propose a modal approach for reasoning about dynamic domains in a logic programming setting. We introduce a language for reasoning about actions which allows procedures to be de ned for building complex actions from elementary actions. The language is able to handle knowledge producing actions as well as actions which remove information. Incomplete states are represented by means of epistemic operators and test actions can be used to check whether a fluent is true, false or undefined in a state. In the language the frame problem is given a non-monotonic solution by making use of persistency assumptions in the context of an abductive characterization. A goal directed proof procedure is defined, which allows to reason about complex actions and to generate conditional plans.

Abstract. Searching for the meaning of the word “personalization ” on a popular search engine, one finds twenty-three different answers, including “the process of matching categorized content with different end users based on business rules... upon page request to a Webserver”, “using continually adjusted user profiles to match content or services to individuals”, and also “real-time tailoring of displays, particularly Web pages, to a specific customer’s known preferences, such as previous purchases”. A little more generally, personalization is a process by which it is possible to give the user optimal support in accessing, retrieving, and storing information, where solutions are built so as to fit the preferences, the characteristics and the taste of the individual. This result can be achieved only by exploiting machine-interpretable semantic information, e.g. about the possible resources, about the user him/herself, about the context, about the goal of the interaction. Personalization is realized by an inferencing process applied to the semantic information, which can be carried out in many different ways depending on the specific task. The objective of this paper is to provide a coherent introduction into issues and methods for realizing personalization in the Semantic Web. 1

. In this paper we propose a modal approach for reasoning about actions in a logic programming framework. We introduce a modal language which makes use of abductive assumptions to deal with persistency, and provides a solution to the ramification problem, by allowing one-way "causal rules" to be defined among fluents. We define the abductive semantics of the language and a goal directed abductive proof procedure to compute abductive solutions for a goal from a given domain description. Both the semantics and the procedure are defined within the argumentation framework. In particular, we focus on a specific semantics, which is essentially an extension of Dung's admissibility semantics to a modal setting. The proof procedure is proved to be sound with respect to this semantics. 1 Introduction Reasoning about a world dynamically changing under effects of actions is one of the central problems of knowledge representation. In this context, starting from Gelfond and Lifschitz' w...

In this paper we propose a modal approach for reasoning about dynamic domains in a logic programming setting. In particular we define a language, called DyLOG, in which actions are naturally represented by modal operators. DyLOG is a language for reasoning about actions which allows to deal with ramifications and to define procedures to build complex actions from elementary ones. Procedure definitions can be easily specified in the modal language by introducing suitable axioms. In the language the frame problem is given a non-monotonic solution by making use of persistency assumptions in the context of an abductive characterization. Moreover, a goal directed proof procedure is defined, which allows to compute a query from a given dynamic domain description. 1 Introduction Reasoning about the effects of actions in a dynamically changing world is one of the main problems which must be faced by intelligent agents. Most of the approaches which have been developed to model action...

The Semantic Web vision of a next generation Web, in which machines are enabled to understand the meaning of information in order to better interoperate and better support humans in carrying out their tasks, is very appealing and fosters the imagination of smarter applications that can retrieve, process and present information in enhanced ways. In this vision, a particular attention should be devoted to personalization: By bringing the user's needs into the center of interaction processes, personalized Web systems overcome the one-size-fits-all paradigm and provide individually optimized access to Web data and information. In this paper, we provide an overview of recent trends for establishing personalization on the Semantic Web: Based on a discussion on reasoning with rule- and query languages for the Semantic Web, we outline an architecture for service-based personalization, and show results in personalizing Web applications.

this paper we describe how a theory for reasoning about actions can be used for specifying agents and for executing agent specifications. In fact, reasoning about the effects of actions in a dynamically changing world is one of the main problems which must be faced by intelligent agents. Furthermore, the internal dynamics of the agent itself can be regarded as resulting from the execution of actions on the mental state. The agent mental state contains all its basic attitudes, as its belief, desires and intentions in the BDI model [13].