This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
One of the surprising findings from the study of CNF satisfiability in the 1990's has been the success of iterative repair techniques, and in particular of weighted iterative...
We describe a general approach to optimization which we term Squeaky Wheel" Optimization SWO. In SWO, a greedy algorithm is used to construct a solution which is then analyze...
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
In this paper, we describe methods for e ciently computing better solutions to control problems in continuous state spaces. We provide algorithms that exploit online search to boo...