Názov:Learning Parallel Portfolios of Algorithms
Vedúci:RNDr. Mikular Popper
Kµúčové slová:AI, Algorithms, Machine Learning, Vapnik-Chervonenkis, Markov Decision Process, Portfolios
Abstrakt:I present Parallel Portfolios of Algorithms (PPA) as an approach to enhance the performance of algorithms. The main idea is to execute several algorithms for the same problem concurrently. I show how to determine the optimal execution schedules of PPA with regard to a sample set of instances. I also provide theoretical distribution-free bounds for generalization probability, and a practical evaluation on SAT problem. In the SAT domain, PPA turned out to be generally 2 times as fast as the fastest algorithm in the portfolio.

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