Solver research direction · rosejn/cortex#254

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説明

We demonstrate this exponential gain by comparing a sequential MatLab implementation of our solver with the winners of the 2016 Max-SAT competition on a variety of hard optimization instances. We show empirical evidence that our solver scales linearly with the size of the problem, both in time and memory, and argue that this property derives from the collective behavior of the simulated physical circuit. Our approach can be applied to other types of optimization problems and the results presented here have far-reaching consequences in many fields.

コントリビューターガイド

技術スタック: なし
領域: machine learning
Issue 種別: research
難度: 5
推定時間: over 1 week
活動状況: stale
明確さ: unclear
前提条件: Understanding of Max SAT problemsFamiliarity with the referenced paperKnowledge of ClojureBackground in optimization algorithms
初心者向け度: 10
調査方針: This issue proposes implementing a Max SAT solver based on the paper 'The Divide and Conquer Approach to Max SAT' (arXiv:1710.09278). The first step is to review the paper and understand the algorithm. Then, a prototype should be developed in the cortex framework, likely in Clojure. The implementation should be evaluated against existing Max SAT benchmarks.