The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
Abstract. We present a parameterized approximation scheme for distributed combinatorial optimization problems based on dynamic programming. The algorithm is a utility propagation m...
We develop exact and approximate algorithms for computing optimal separators and measuring the extent to which two point sets in d-dimensional space are separated, with respect to...
Recent results on the local and global properties of multisymplectic discretizations of Hamiltonian PDEs are discussed. We consider multisymplectic (MS) schemes based on Fourier s...
Given a polygonal path P with vertices p1, p2, . . . , pn and a real number t ≥ 1, a path Q = (pi1 , pi2 , . . . , pik ) is a t-distance-preserving approximation of P if 1 = i1 &...
Joachim Gudmundsson, Giri Narasimhan, Michiel H. M...