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In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains. In many cases, we have developed new ways of viewing the problem that are, perhaps, more consistent with the AI perspective. We begin by introducing the theory of Markov decision processes (Mdps) and partially observable Markov decision processes...
Previous approaches to robustness in natural language processing usually treat deviant input by relaxing grammatical constraints whenever a successful analysis cannot be provided by “normal” means. This schema implies, that error detection always comes prior to error handling, a behaviour which hardly can compete with its human model, where many erroneous situations are treated without even noticing...
Intelligent systems can be modeled by organizationally closed networks of interacting agents. An interesting step in the evolution from agents to systems of agents is to approach logic itself as a system of autonomous elementary processes called distinctions. Distinction networks are directed acyclic graphs in which links represent logical implication and nodes are autonomous agents which act in response...
This paper explores and reasons about the interplay between symbolic and continuous representations. We first provide some historical perspective on the signal and symbol integration as viewed by the Artificial Intelligence (AI), Robotics and Computer Vision communities. The domain of autonomous robotic agents residing in the dynamically changing environments anchors well different aspects of this...
Methods of Explanation-Based Generalization (EBG) within a logic-programming environment, such as McCarty and Kedar-Cabelli's PROLOG-EBG algorithm [KCMcC87], require the domain theory to be represented as a definite, i.e. Horn clause program. The same restriction holds for Siqueira and Puget's Explanation-Based Generalization of Failures [SiPu88]. However, a number of practical applications can be...
Integrity constraints are important logical tools for the general organization of knowledge. Integrity constraints (in short: ICs), which are commonly used in the field of deductive databases, specify general regularities like “a son is not older than his father.” They facilitate the organization of knowledge in expert systems and can speed up the query-response time significantly. This paper...
The dynamic knowledge structuring concept outlined in this paper contributes to the reusability of hetereogeneous lexical resources. I present a dynamic organization of lexical knowledge in a knowledge packet (KP) structure extended by local converters. A dynamic organization is an adequate mechanism to mediate between the diversity of already given and newly introduced lexical resources. Moreover...
In this paper we present a heuristic search algorithm, DBIDA*, which uses a given, bounded memory of size m. Previously published algorithms like IDA*, IDA*-CR, MA*, SMA*, etc. expand up to Ω(n2) nodes, where n is the number of nodes expanded by A*, or suffers from an high overhead per node expansion which limits their applicability to practical problems. We show that our algorithm...
We introduce a qualitative methodology for concept learning from texts that relies upon second-order reasoning about statements expressed in a (first-order) terminological representation language. This meta-reasoning approach allows for quality-based evaluation and selection among alternative concept hypotheses.
In many knowledge based systems the application domain is modeled in an object-centered formalism. Research in knowledge acquisition has given evidence that this approach allows one to adequately model the conceptual structures of human experts. However, when a novice user wants to describe a particular task to be solved by such a system he has to be well acquainted with the underlying domain model,...
Description Logics (DL), one of the major paradigms in Knowledge Representation, face efficiency problems due to large-scale applications, expressive dialects, or complete inference algorithms. In this paper we investigate the potential of parallelizing DL algorithms to meet this challenge. Instead of relying on a parallelism inherent in logic programming languages, we propose to exploit the application-specific...
This paper deals with the automation of termination proofs for recursively defined algorithms (i.e. algorithms in a pure functional language). Previously developed methods for their termination proofs either had a low degree of automation or they were restricted to one single fixed measure function to compare data objects. To overcome these drawbacks we introduce a calculus for automated termination...
We investigate the task of skeptically reasoning in extension-based, nonmonotonic logics by concentrating on general argumentation theories. The restricted applicability of Dung's notion of skeptical provability in his well-known argumentation framework is illustrated, and a new approach based on the notion of a claim associated with each argument is proposed. We provide a formal definition of a skeptical...
In this paper we study the dynamics of belief from an agent-oriented, semantics-based point of view. In a formal framework used to specify and to analyze rational agents, we define actions that model three well-known changes of belief, viz. expansions, contractions and revisions. We define both the opportunity for and the result of these belief-changing actions. To define the semantics of the contraction...
The formalization of reasoning about action and change is one of the central problems in the theory of knowledge representation. Strangely enough, no much interest has been attracted to investigate scenario problems involving actions with default effects. In everyday life people often undertake actions which have expected, yet not necessarily certain results. Modelling a behaviour of intelligent agents,...
We present a logic-based method for reasoning about action and change. In contrast to most of the other approaches aimed at this kind of inference, our proposal admits actions with abnormal effects. More specifically, with each action A we associate a pair of specifications, S1 and S2, representing respectively normal and abnormal performance of A. The intention is that each...
This paper presents an approach to temporal knowledge representation based on reified propositional logic, where times qualifications are interpreted as Characteristic Functions. A characteristic function is a (possibly partial) function describing for what instants of time a logical property holds (or does not hold) — thus it refers to the idea of characteristic function of a set. The calculus is...
While the computational properties of qualitative temporal reasoning have been analyzed quite thoroughly, the computational properties of qualitative spatial reasoning are not very well investigated. In fact, almost no completeness results are known for qualitative spatial calculi and no computational complexity analysis has been carried out yet. In this paper, we will focus on the so-called RCC approach...
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