We give efficient algorithms to sample uniformly, and count approximately, the solutions to a zero-one knapsack problem. The algorithm is based on using dynamic programming to pro...
We present deterministic sequences for use in sampling-based approaches to motion planning. They simultaneously combine the qualities found in many other sequences: i) the increme...
In this paper, we present a parallel algorithm for the minimization of deterministic finite state automata (DFA's) and discuss its implementation on a connection machine CM-5...
We study the problem of allocating a set of indivisible items to players having additive utility functions over the items. We consider allocations in which no player envies the bun...
Ioannis Caragiannis, Christos Kaklamanis, Panagiot...
This paper proposes an optimal approach to infinite-state action planning exploiting automata theory. State sets and actions are characterized by Presburger formulas and represent...