We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
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...
As some cognitive research suggests, in the process of learning languages, in addition to overt explicit negative evidence, a child often receives covert explicit evidence in form...
Building a bilingual dictionary for transfer in a machine translation system is conventionally done by hand and is very time-consuming. In order to overcome this bottleneck, we pr...
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...