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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).

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

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

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Optimisation of Separable Functions Which problems modelled by separable functions are solvable efficiently?

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PowAlgDO To provide precise characterisations of the applicability of convex relaxations, and to d…

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Dueling Network Architectures for Deep Reinforcement Learning

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