This paper explores the hypothesis that pointing gesture recognition can be learned using a reward based system. An experiment with two four-legged robots is presented. One of the...
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...
Most conventional Policy Gradient Reinforcement Learning (PGRL) algorithms neglect (or do not explicitly make use of) a term in the average reward gradient with respect to the pol...
Trust negotiation is an approach to establishing trust between strangers through the bilateral, iterative disclosure of digital credentials. Under automated trust negotiation, acc...
In designing Markov Decision Processes (MDP), one must define the world, its dynamics, a set of actions, and a reward function. MDPs are often applied in situations where there i...
David L. Roberts, Sooraj Bhat, Kenneth St. Clair, ...