We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [1...
Joint attention is one of the most important cognitive functions for the emergence of communication not only between humans but also between humans and robots. In the previous wor...
Both academic institutions and businesses are exploring a shift from face-to-face instruction to distance learning. However, without the foundation of a systematic instructional d...
We propose a bootstrapping approach to training a memoriless stochastic transducer for the task of extracting transliterations from an English-Arabic bitext. The transducer learns...