We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
In this paper we describe a way to save and restore the state of a running Java program. We achieve this on the language level, without modifying the Java virtual machine, by instr...
Effective operational control of a manufacturing system that has routing flexibility is dependent upon being able to make informed real-time decisions in the event of a system dis...
Catherine M. Harmonosky, Robert H. Farr, Ming-Chua...
Objects model the world, and state is fundamental to a faithful modeling. Engineers use state machines to understand and reason about state transitions, but programming languages ...
Jonathan Aldrich, Joshua Sunshine, Darpan Saini, Z...