In this paper we discuss the need for learning in multi-agent design systems, and the variety of forms it might take. We propose a particular method of guiding learning in these s...
We present the first large-scale empirical application of reinforcement learning to the important problem of optimized trade execution in modern financial markets. Our experiments...
Abstract. Traditionally, machine learning algorithms such as decision tree learners have employed attribute-value representations. From the early 80's on people have started t...
In Artificial Intelligence with Coalition Structure Generation (CSG) one refers to those cooperative complex problems that require to find an optimal partition, maximising a soci...
Nicola Di Mauro, Teresa Maria Altomare Basile, Ste...