ion in probabilistic domains has long been rec-ognizedas an effective tool to faciliate faster reasoning.In this paper we focused on the technical side of ob-taining a correct macro abstraction; a comprehensivetheory of abstracting probabilistic actions is presentedin [2]. Empirical results of applying the technique toseveral domains showed substantial reduction in t...

This paper addresses a new version of the exible ow line prob- lem, i.e., the budget constrained one, in order to determine the required num- ber of processors at each station along with the selection of the most eco- nomical process routes for products. Since a number of parameters, such as due dates, the amount of available budgets and the cost of opting particular routes, are imprecise (fuzz...

We address the problem of nding a tight representation of com plex logical constraints in a mixed integer programming model by de scribing a convex hull representation of cardinality rules A cardinality rule asserts that if at least k of the propositions A Am are true then at least l of the propositions B Bn are true As rule based systems and other types of logic modeling grow in popu larity lo...

Point = fx,y: Integer;CompareType <= Point;equal(p: CompareType): Bool freturn (this.x=p.x) and (this.y=p.y);ggPoint = AbstractPoint fCompareType = Point;gColourPoint = AbstractPoint fc: Color;CompareType = ColourPoint;equal(p: CompareType): Bool freturn super.equal(p) and (this.c = p.c);gg Figure 13: A slight change xes the problemOn ...

ions introduced from outside the system (ancestors) to those created internally using the former ones (progenies) [5]. A trace is a simpli ed version of our metaprogram construct. A trace has a path and a body. The path speci es the elements of the system that should be a ected, while the body speci es how they should be a ected by the introduction of the special behavior. However, traces do no...

This paper concerns building embedded languages in Prolog, with special attention on expert system shells. First, the paradigm of meta-programming, of which building embedded languages is an example, is discussed. Second, we review interpreters for embed­ ded languages, concentrating on meta-interpreters. Fi­ nally, two applications, explanation and uncertainty reasoning, are presented and the ...

Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments These algorithms including the TD algo rithm of Sutton and the Q learning algorithm of Watkins can be motivated heuristically as approximations to dynamic program ming DP In this paper we provide a rigorous proof of convergence of these DP ba...

Practical algorithmicmethods for combinatorial optimization prob lems cannot be considered in isolation from the representations that people use when communicating these problems to computer systems Di erent represen tations de ne di erent problem classes for which distinct types of methods are appropriate Conversely di erent methods have di erent ranges of applicabil ity which have motivated a...

We provide an analytical comparison between discounted and average reward temporal di erence TD learning with linearly parameterized approximations We rst consider the asymptotic behavior of the two algorithms We show that as the discount factor approaches the value function produced by discounted TD approaches the di erential value function generated by average reward TD We further argue that ...

he motivation behind multi-relational data mining is wledge discovery in relational databases containing tiple related tables. One difficulty relational data ing faces is managing intractably large hypothesis ces. We attempt to overcome this difficulty by first pling the hypothesis space. We generate a small set of otheses, uniformly sampled from the space of didate hypotheses, and evaluate thi...