Seminar Details

Numerous problems in computer science and combinatorics can be formulated as searching for objects lacking certain bad properties, or "flaws". For example, constraint satisfaction problems like satisfiability can be seen as searching for objects (truth assignments) that are flawless in the sense that they do not violate any constraint. A large class of practical algorithms for finding flawless objects employ "stochastic local search"; such algorithms start with a flawed object and try to make it flawless via small randomized changes that in each step focus on eradicating a specific flaw (while potentially introducing others).

In this talk, I will present a general framework for the design and analysis of stochastic local search algorithms, inspired by and extending the Lovasz Local Lemma.  I will also talk about its applications in solving  "pseudo-random" instances of constraint satisfaction problems.