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Algorithms and Complexity Theory

Research in Algorithms and Complexity Theory includes determining the inherent difficulty of computational problems, classifying problems according to this inherent difficulty, and designing and analysing algorithms that use computational resources as efficiently as possible. Within this context, the Algorithms and Complexity Theory group at Oxford has particular interest in the following topics:

  • algorithmic game theory and computational economics
  • circuit complexity
  • computational counting problems
  • constraint satisfaction problems
  • exact algorithms and fine-grained complexity
  • foundational issues in computational learning
  • online algorithms, and
  • randomised algorithms (including the analysis of stochastic processes, the probabilistic analysis of algorithms and pseudorandomness).

Related seminar series

All Activities

Activities

Constraint Satisfaction Problems Computational problems from many different application areas can be s…

Read more about Constraint Satisfaction Problems

Algorithmic Game Theory and Computational Economics Investigating problems such as finding Nash Equilibria and games with…

Read more about Algorithmic Game Theory and Computational Economics

All Projects

Projects

NAASP Constraint satisfaction problems (CSPs) have driven some of the most influential developm…

Read more about NAASP

Proof complexity and circuit complexity: a unified approach

Read more about Proof complexity and circuit complexity: a unified approach

All Publications

Publications

Recursion and Sequentiality in Categories of Sheaves

Read more about Recursion and Sequentiality in Categories of Sheaves

Effect algebras‚ presheaves‚ non−locality and contextuality

Read more about Effect algebras‚ presheaves‚ non−locality and contextuality

Research