Many important combinatorial optimization problems can be expressed as constraint satisfaction problems with soft constraints. When problems are too difficult to be solved exactly,...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
A key problem for effective unit testing is the difficulty of partitioning large software systems into appropriate units that can be tested in isolation. We present an approach th...
Certain hard real-time tasks demand precise timing of events, but the usual software solution of periodic interrupts driving a scheduler only provides precision in the millisecond ...
Abstract. This work introduces a new analytical method for performance evaluation of wireless packet-oriented networks. Unlike traditional call admission control procedures commonl...