Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
Partially observable Markov decision processes (pomdp's) model decision problems in which an agent tries to maximize its reward in the face of limited and/or noisy sensor fee...
Michael L. Littman, Anthony R. Cassandra, Leslie P...
In this paper, we describe the brain activities that are associated with emoticons by using functional MRI (fMRI). In communication over a computer network, we use faces such as c...
We present a method for performing selection tasks based on continuous control of multiple, competing agents who try to determine the user's intentions from their control beh...
Semantic Web, the next generation of Web, gives data well-defined and machine-understandable meaning so that they can be processed by remote intelligent agents cooperatively. Onto...
Jin Song Dong, Chew Hung Lee, Yuan-Fang Li, Hai H....