Previous studies have demonstrated that encoding a Bayesian network into a SAT formula and then performing weighted model counting using a backtracking search algorithm can be an ...
Constraint satisfaction and propositional satisfiability problems are often solved using backtracking search. Previous studies have shown that portfolios of backtracking algorith...
In the model-based policy search approach to reinforcement learning (RL), policies are found using a model (or "simulator") of the Markov decision process. However, for ...
Abstract--The Distributed Stochastic Algorithm (DSA), Distributed Breakout Algorithm (DBA), and variations such as Distributed Simulated Annealing (DSAN), MGM-1, and DisPeL, are di...
An efficient policy search algorithm should estimate the local gradient of the objective function, with respect to the policy parameters, from as few trials as possible. Whereas m...