Satisfiability Lower Bounds and Tight Results for Parameterized and Exponential-Time Algorithms

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source: Simons Institute     2015年11月10日
Satisfiability Lower Bounds and Tight Results for Parameterized and Exponential-Time Algorithms
Nov. 2 – Nov. 6, 2015
During the last decade, it has been recognized that the complexity assumption known as the (Strong) Exponential Time Hypothesis on satisfiability can explain the complexity of a large number of computational problems in a tight way, showing the optimality of known algorithms. This connection has transformed the field of parameterized complexity by refining the question of which problems are fixed-parameter tractable to a fine-grained optimality program that tries to determine the best possible running time for all problems. Recent results show that such an understanding is possible for a wide range of problems, but there are still no tight bounds in many cases. This indicates that further work is needed on understanding the complexity assumptions related to satisfiability, transferring these lower bounds to various specific problem domains, and obtaining matching algorithmic upper bounds. The goal of the workshop is to bring together researchers from satisfiability, classical computational complexity, parameterized complexity and algorithm design to present recent results in these areas and initiate a discussion on connections between the complexity of satisfiability and the fine-grained complexity of other problems, and their implications for algorithm design.
For more information, please visit https://simons.berkeley.edu/workshops/complexity2015-2.
These presentations were supported in part by an award from the Simons Foundation.

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