TL;DR
This paper explores how practical computing advances can inform complexity theory and algorithms, discussing the use of linear program solvers for lower bounds and proposing a research agenda for circuit complexity.
Contribution
It provides an overview of integrating practical computing with theoretical complexity, and suggests new directions for research in circuit complexity and lower bounds.
Findings
Linear program solvers can aid in proving satisfiability lower bounds
Practical computing methods can inform complexity theory
A new research program for circuit complexity is proposed
Abstract
How can complexity theory and algorithms benefit from practical advances in computing? We give a short overview of some prior work using practical computing to attack problems in computational complexity and algorithms, informally describe how linear program solvers may be used to help prove new lower bounds for satisfiability, and suggest a research program for developing new understanding in circuit complexity.
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Computational Geometry and Mesh Generation · Advanced Graph Theory Research