Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Real-time rendering of triangulated surfaces has attracted growing interest in the last few years. However, interactive visualization of very large scale grid digital elevation mo...
Abstract--This paper proposes an analytical model to estimate the cost of running an affinity-based thread schedule on multicore systems. The model consists of three submodels to e...
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
We present a new constructive solving approach for systems of 3D geometric constraints. The solver is based on the cluster rewriting approach, which can efficiently solve large sy...