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arXiv · 2107.11784

Power of human-algorithm collaboration in solving combinatorial optimization problems

Tapani Toivonen
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Abstract

Many combinatorial optimization problems are often considered intractable to solve exactly or by approximation. An example of such problem is maximum clique which -- under standard assumptions in complexity theory -- cannot be solved in sub-exponential time or be approximated within polynomial factor efficiently. We show that if a polynomial time algorithm can query informative Gaussian priors from an expert $poly(n)$ times, then a class of combinatorial optimization problems can be solved efficiently in expectation up to a multiplicative factor $\epsilon$ where $\epsilon$ is arbitrary constant. While our proposed methods are merely theoretical, they cast new light on how to approach solving these problems that have been usually considered intractable.

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Tapani Toivonen. 2021-07-25. Power of human-algorithm collaboration in solving combinatorial optimization problems. https://arxiv.org/abs/2107.11784

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