A Natural Evolution Strategy for Multi-objective Optimization

Abstract. The recently introduced family of natural evolution strategies (NES), a novel stochastic descent method employing the natural gradient, is providing a more principled alternative to the well-known covariance matrix adaptation evolution strategy (CMA-ES). Until now, NES could only be used for single-objective optimization. This paper extends the approach to the multi-objective case, by first deriving a (1+1) hillclimber version of NES which is then used as the core component of a multi-objective optimization algorithm. We empirically evaluate the approach on a battery of benchmark functions and find it to be competitive with the state-of-the-art.

• Type: Journal
• Year: 2010
• Where: PPSN
• Authors: Tobias Glasmachers, Tom Schaul, Jürgen Schmidhuber
• Keywords: Adaptation Evolution Strategy, Distributed And Parallel Computing, Natural Evolution Strategies, PPSN 2010, Well-known Covariance Matrix