Published January 4, 2021 | Version Accepted pre-print
Book chapter Open

Quality-Diversity Optimization: a novel branch of stochastic optimization

  • 1. Computer Technology Institute & Press "Diophantus" (CTI)PatrasGreece
  • 2. Adaptive & Intelligent Robotics LabImperial College LondonLondonUK
  • 3. CYENS Centre of ExcellenceNicosiaCyprus
  • 4. Inria, CNRSUniversité de Lorraine, LORIANancyFrance


Traditional optimization algorithms search for a single global optimum
that maximizes (or minimizes) the objective function. Multimodal optimization algorithms
search for the highest peaks in the search space that can be more than one.
Quality-Diversity algorithms are a recent addition to the evolutionary computation
toolbox that do not only search for a single set of local optima, but instead try to illuminate
the search space. In effect, they provide a holistic view of how high-performing
solutions are distributed throughout a search space. The main differences with multimodal
optimization algorithms are that (1) Quality-Diversity typically works in the
behavioral space (or feature space), and not in the genotypic (or parameter) space,
and (2) Quality-Diversity attempts to fill the whole behavior space, even if the niche
is not a peak in the fitness landscape. In this chapter, we provide a gentle introduction
to Quality-Diversity optimization, discuss the main representative algorithms, and
the main current topics under consideration in the community. Throughout the chapter,
we also discuss several successful applications of Quality-Diversity algorithms,
including deep learning, robotics, and reinforcement learning.


This work has been partly supported by the project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 739578 (RISE – Call: H2020-WIDESPREAD-01-2016-2017-TeamingPhase2) and the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy.


Chatzilygeroudis_et_al_2021_Chapter_Quality-DiversityOptimization (1).pdf

Additional details


RISE – Research Center on Interactive Media, Smart System and Emerging Technologies 739578
European Commission