To better represent human interactions in social networks, the authors take a network-oriented simulation approach to analyze the evolution of acquaintance networks based on local...
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
We address the problem of online route discovery for a class of graphs that can be embedded either in two or in three dimensional space. In two dimensions we propose the class of ...
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...