This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Most features in commercial simulation packages are often omitted in parallel simulation benchmarks, because they neither affect the overall correctness of the simulation protocol...
This paper discusses three techniques useful in relaxing the constraints imposed by control flow on parallelism: control dependence analysis, executing multiple flows of control s...
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
A central challenge in computer science and knowledge representation is the integration of conceptual frameworks for continuous and discrete change, as exemplified by the theory ...