Computers have already eclipsed the level of human play in competitive Scrabble, but there remains room for improvement. In particular, there is much to be gained by incorporating...
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms ha...
This paper proposes a stochastic dynamic thermal management (DTM) technique in high-performance VLSI system with especial attention to the uncertainty in temperature observation. ...
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...