In this paper, we consider the problem of policy evaluation for continuousstate systems. We present a non-parametric approach to policy evaluation, which uses kernel density estimation to represent the system. The true form of the value function for this model can be determined, and can be computed using Galerkin’s method. Furthermore, we also present a unified view of several well-known policy...

where A is a matrix of order m × p and rank m, and A is a real valued parameter. It may be required to solve this problem for all real values of A, or for all values of A in some specified interval of the real line. f(A) is a piecewise linear convex function in A. The simplex algorithm for this parametric linear program partitions the real line into intervals, each interval being the optimality...

We present an approximation method for inventory management under multiple suppliers and stochastic lead times. The method is based on parametric dynamic programming using convex piecewise linear approximations of the differential cost function in approximate relative value iteration steps and works for a range of stochastic control problems with linear dynamics and convex piecewise linear imme...

Disjunctive Logic Programming (DLP) is an advanced formalism for Knowledge Representation and Reasoning (KRR). DLP is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class Σ 2 (NP ). Importantly, the DLP encodings are often simple and natural. In this paper, we single out some limitations of DLP for KR...

The Approximate Linear Programming (ALP) approach to value function approximation for MDPs is a parametric value function approximation method, in that it represents the value function as a linear combination of features which are chosen a priori. Choosing these features can be a difficult challenge in itself. One recent effort, Regularized Approximate Linear Programming (RALP), uses L1 regular...

Current implementations of constraint logic programming languages (like CLP(<), CHIP or RISC-CLP(Real) support constraint solving over a certain xed domain. In this paper a system is presented which gives the possibility to instantiate a constraint logic programming language with an arbitrary constraint domain. The interface between the system and such a constraint domain is given and the exten...

In this paper we discuss how to deal with decision problems that are described with LP models and formulated with elements of imprecision and uncertainty. More precisely, we will study LP models in which the parameters are not fully known but only with some degree of precision. Even with incomplete information the model builder (or model user) is normally able to give a realistic interval for t...

An extension to the Go language was developed that introduces parametric polymorphism in the form of generic functions. The changes to the language and the compiler needed to implement the type system extensions are discussed, and alternative implementation strategies are described. The resulting implementation of generic functions is backwards compatible with the existing Go standard and is co...