Nov 2022· Annual Conference on Genetic and Evolutionary Computation· 3 citations· 172 references
Computer ScienceMathematics
TL;DR
A very general version of Go-Explore is instantiated with promising performance for challenging and computationally expensive objectives, such as arise in simulations.
Abstract
The theory of magnitude provides a mathematical framework for quantifying and maximizing diversity. We apply this framework to formulate quality-diversity algorithms in generic dissimilarity spaces. In particular, we instantiate a very general version of Go-Explore with promising performance for challenging and computationally expensive objectives, such as arise in simulations.
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This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9
