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WalkSAT

Local search algorithm solving boolean satisfiability

In computer science, GSAT and WalkSAT are local search algorithms to solve Boolean satisfiability problems. Both algorithms work on formulae in Boolean

WalkSAT

Local search (constraint satisfaction)

other way, which involves some degree of randomness. The random move of WalkSAT is changing the value of a random variable of a random violated constraint

Local search (constraint satisfaction)

Local_search_(constraint_satisfaction)

Local search (optimization)

Method for problem solving in optimization

engineering, and bioinformatics. Examples of local search algorithms are WalkSAT, the 2-opt algorithm for the traveling salesman problem and the Metropolis–Hastings

Local search (optimization)

Local_search_(optimization)

List of artificial intelligence algorithms

chaining DPLL algorithm Forward chaining Resolution (logic) Rete algorithm WalkSAT Baum–Welch algorithm Belief propagation Expectation–maximization algorithm

List of artificial intelligence algorithms

List_of_artificial_intelligence_algorithms

Hamming ball

Set of strings with few differences

whole Hamming space. Some local search algorithms for SAT solvers such as WalkSAT operate by using random guessing or covering codes to find a Hamming ball

Hamming ball

Hamming_ball

Exponential time hypothesis

Unproven computational hardness assumption

exponential function depending on k {\displaystyle k} . For instance, the WalkSAT probabilistic algorithm can solve k {\displaystyle k} -SAT in average time

Exponential time hypothesis

Exponential_time_hypothesis

Satplan

Method for automated planning

a method for establishing satisfiability such as the DPLL algorithm or WalkSAT. The process encodes key elements of the planning problem—initial state

Satplan

Proof of work

System that regulates the formation of blocks on a blockchain

PoUW component. The paper gives an example that implements a variant of WalkSAT, a local search algorithm to solve Boolean problems. Optimisable proof

Proof of work

Proof_of_work

SAT solver

Computer program for the Boolean satisfiability problem

DPLL family include stochastic local search algorithms. One example is WalkSAT. Stochastic methods try to find a satisfying interpretation but cannot

SAT solver

SAT_solver

Boolean satisfiability problem

Problem of determining if a Boolean formula could be made true

clause learning (CDCL), and stochastic local search algorithms such as WalkSAT. Almost all SAT solvers include time-outs, so they will terminate in reasonable

Boolean satisfiability problem

Boolean_satisfiability_problem

Symbolic artificial intelligence

Methods in artificial intelligence research

Monte Carlo Search. Key search algorithms for Boolean satisfiability are WalkSAT, conflict-driven clause learning, and the DPLL algorithm. For adversarial

Symbolic artificial intelligence

Symbolic_artificial_intelligence

Algorithmic Lovász local lemma

On constructing objects that obey a system of constraints with limited dependence

algorithm is similar to WalkSAT which is used to solve general boolean satisfiability problems. The main difference is that in WalkSAT, after the unsatisfied

Algorithmic Lovász local lemma

Algorithmic_Lovász_local_lemma

Boolean satisfiability algorithm heuristics

by the PCP theorem unless P = NP. Other stochastic SAT solvers, such as WalkSAT and GSAT are an improvement to the above procedure. They start by randomly

Boolean satisfiability algorithm heuristics

Boolean_satisfiability_algorithm_heuristics

Bart Selman

American computer scientist

compilation, planning, default reasoning, satisfiability solvers like WalkSAT, and connections between computer science and statistical physics, namely

Bart Selman

Bart_Selman

Uwe Schöning

German computer scientist (born 1955)

monograph with Köbler and Toran. In a 1999 FOCS paper, Schöning showed that WalkSAT, a randomized algorithm previously analyzed for 2-satisfiability by Papadimitriou

Uwe Schöning

Uwe_Schöning