rosejn/cortex

Solver research direction

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#254 建立於 2017年12月28日

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 (5 留言) (0 反應) (0 負責人)Clojure (1,269 star) (109 fork)batch import
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描述

https://arxiv.org/abs/1710.09278

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.

貢獻者指南

技術棧
無
領域
machine learning
議題類型
research
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
5
預計時間有經驗貢獻者完成調查、實作、測試並準備 pull request 的粗略時間範圍。
over 1 week
活動狀態議題目前的可參與程度：新鮮、活躍、陳舊、阻塞或等待維護者輸入。
stale
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
unclear
前置要求
Understanding of Max SAT problemsFamiliarity with the referenced paperKnowledge of ClojureBackground in optimization algorithms
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
10
研究方向
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.