Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
Chris Gaskett, David Wettergreen, Alexander Zelins...
An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts to decompose and solve a model-free factored MDP h...
This paper investigates the problem of designing decentralized representations to support monitoring and inferences in sensor networks. State-space models of physical phenomena su...
Juan Liu, Maurice Chu, Jie Liu, Jim Reich, Feng Zh...
Abstract. We compare three specification frameworks for the operationtics of programming languages, abstract state machines (ASMs) and the two incarnations of natural semantics, b...
In the field of DNA computing, more and more efforts are made for constructing molecular machines made of DNA that work in vitro or in vivo. States of some of those machines are...