Stochastic Search and Phase Transitions: AI Meets Physics
نویسنده
چکیده
Computationally hard instances of combinatorial problems arise at a certain critical ratio of constraints to variables. At the critical ratio, problem distributions undergo dramatic changes. I will discuss how an analogous phenomenon occurs in phase transitions studied in physics, and how experiments with critically constrained problems have led to surprising new insights into average-case complexity and stochastic search methods in AI.
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