Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...
Many practical optimization problems are constrained black boxes. Covariance Matrix Adaptation Evolution Strategies (CMA-ES) belong to the most successful black box optimization me...
Abstract. In this paper we discuss Evolution Strategies within the context of interactive optimization. Different modes of interaction will be classified and compared. A focus will...
In this paper, we consider the optimality of beamforming for achieving the ergodic capacity of multiple-input multiple-output (MIMO) multiple access channel (MAC) via virtual repre...
In this paper we present the application of an evolution strategy to the problem of detecting multi-planet transit events in photometric time-data series. Planetary transits occur...