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A New Method for Solving Hard Satisfiability Problems
A greedy local search procedure called GSAT is introduced for solving propositional satisfiability problems and its good performance suggests that it may be advantageous to reformulate reasoning tasks that have traditionally been viewed as theorem-proving problems as model-finding tasks. Expand
Noise Strategies for Improving Local Search
It is shown that mixed random walk is the superior strategy for solving MAX-SAT problems, and results demonstrating the effectiveness of local search with walk for solving circuit synthesis and circuit diagnosis problems are presented. Expand
Hard and Easy Distributions of SAT Problems
It is shown that by using the right distribution of instances, and appropriate parameter values, it is possible to generate random formulas that are hard, that is, for which satisfiability testing is quite difficult. Expand
Pushing the Envelope: Planning, Propositional Logic and Stochastic Search
Stochastic methods are shown to be very effective on a wide range of scheduling problems, but this is the first demonstration of its power on truly challenging classical planning instances. Expand
Local search strategies for satisfiability testing
The power of local search for satissability testing can be further enhanced by employing a new strategy, called mixed random walk, for escaping from local minima, which allows us to handle formulas that are substantially larger than those that can be solved with basic local search. Expand
Planning as Satisfiability
SATPLAN04 is a updated version of the planning as satisfiability approach originally proposed in (Kautz & Selman 1992; 1996) using hand-generated translations, and implemented for PDDL input in theExpand
Unstructured human activity detection from RGBD images
This paper uses a RGBD sensor as the input sensor, and compute a set of features based on human pose and motion, as well as based on image and point-cloud information, based on a hierarchical maximum entropy Markov model (MEMM). Expand
Evidence for Invariants in Local Search
This work presents two statistical measures of the local search process that allow one to quickly find the optimal noise settings, and applies these principles to the problem of evaluating new search heuristics, and discovered two promising new strategies. Expand
Unifying SAT-based and Graph-based Planning
It is shown that STRIPS problems can be directly translated into SAT and efficiently solved using new randomized systematic solvers and that polynomialtime SAT simplification algorithms applied to the encoded problem instances are a powerful complement to the "mutex" propagation algorithm that works directly on the plan graph. Expand
Referral Web: combining social networks and collaborative filtering
Part of the success of social networks can be attributed to the “six degrees of separation’’ phenomena that means the distance between any two individuals in terms of direct personal relationships isExpand