• Media type: E-Article; Electronic Conference Proceeding; Text
  • Title: Thinking Algorithmically About Impossibility (Invited Talk)
  • Contributor: Williams, R. Ryan [Author]
  • imprint: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2015
  • Language: English
  • DOI: https://doi.org/10.4230/LIPIcs.CSL.2015.14
  • Keywords: circuit complexity ; satisfiability ; derandomization
  • Origination:
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  • Description: Complexity lower bounds like P != NP assert impossibility results for all possible programs of some restricted form. As there are presently enormous gaps in our lower bound knowledge, a central question on the minds of today's complexity theorists is how will we find better ways to reason about all efficient programs? I argue that some progress can be made by (very deliberately) thinking algorithmically about lower bounds. Slightly more precisely, to prove a lower bound against some class C of programs, we can start by treating C as a set of inputs to another (larger) process, which is intended to perform some basic analysis of programs in C. By carefully studying the algorithmic "meta-analysis" of programs in C, we can learn more about the limitations of the programs being analyzed. This essay is mostly self-contained; scant knowledge is assumed of the reader.
  • Access State: Open Access