R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Discrete Event Simulation (DES) has been used as a design and validation tool in various production and business applications. DES can also be utilized for analyzing the product-m...
The problem of searching for important factors in a simulation model is considered when the simulation output is subject to stochastic variation. Bettonvil and Kleijnen (1996) giv...
We present a biologically inspired approach to the dynamic assignment and reassignment of a homogeneous swarm of robots to multiple locations, which is relevant to applications lik...