Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
Scientific programs rely heavily on software libraries. This paper describes the limitations of this reliance and shows how it degrades software quality. We offer a solution that u...
An improved method for expressing the greatest common divisor of n numbers as an integer linear combination of the numbers is presented and analyzed, both theoretically and practi...
In this paper we consider a problem that occurs when drawing public transportation networks. Given an embedded graph G = (V, E) (e.g. the railroad network) and a set H of paths in...
Matthew Asquith, Joachim Gudmundsson, Damian Merri...
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
Zhengzhu Feng, Richard Dearden, Nicolas Meuleau, R...