Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Abstract— This study proposes a Batch-Learning SelfOrganizing Map with False-Neighbor degree between neurons (called BL-FNSOM). False-neighbor degrees are allocated between adjac...
A series of evolutionary neural network simulations are presented which explore the hypothesis that learning factors can result in the evolution of long periods of parental protec...
This paper is concerned with how multi-agent reinforcement learning algorithms can practically be applied to real-life problems. Recently, a new coordinated multi-agent exploratio...
Digital information economies require information goods producers to learn how to position themselves within a potentially vast product space. Further, the topography of this spac...
Christopher H. Brooks, Robert S. Gazzale, Jeffrey ...