We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Machine learning is a key technology to design and create intelligent systems, products, and related services. Like many other design departments, we are faced with the challenge t...
Bram van der Vlist, Rick van de Westelaken, Christ...
Knowledge elicitation is known to be a difficult task and thus a major bottleneck in building a knowledge base. Machine learning has long ago been proposed as a way to alleviate th...
Martin Mozina, Matej Guid, Jana Krivec, Aleksander...
Abstract. This paper extends the N-person IPD game into a more interesting game in economics, namely, the oligopoly game. Due to its market share dynamics, the oligopoly game is mo...
When modeling high-dimensional richly structured data, it is often the case that the distribution defined by the Deep Boltzmann Machine (DBM) has a rough energy landscape with man...