Quality diversity

Evolution, Reinforcement learning, Search algorithms
(Pugh, Soros, and Stanley 2016; Cully and Demiris 2017)

QD is about creating algorithms that favor diversity in searching the space. In QD, one needs to both:

  • Measure the quality of a solution
  • Have a way to describe the effect of a solution

Solutions in QD have to be good in the two above ways.

QD is also a form of novelty search.


  1. . . "Quality and Diversity Optimization: A Unifying Modular Framework". IEEE Transactions on Evolutionary Computation 22 (2). IEEE:245–59.

  2. . . “Quality Diversity: A New Frontier for Evolutionary Computation”. Frontiers in Robotics and AI 3. Frontiers. DOI.

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