In a sampling problem, we are given an input x {0, 1} n , and asked to sample approximately from a probability distribution Dx over poly (n)-bit strings. In a search problem, we ...
Current state-of-the-art planners solve problems, easy and hard alike, by search, expanding hundreds or thousands of nodes. Yet, given the ability of people to solve easy problems...
Automatedreasoning or theorem proving essentially amounts to solving search problems. Despite significant progress in recent years theorem provers still have manyshortcomings. The...
Recent dynamic local search (DLS) algorithms such as SAPS are amongst the state-of-the-art methods for solving the propositional satisfiability problem (SAT). DLS algorithms modi...
Cognitive architectures aspire for generality both in terms of problem solving and learning across a range of problems, yet to date few examples of domain independent learning has...