We propose a new classification for multi-agent learning algorithms, with each league of players characterized by both their possible strategies and possible beliefs. Using this c...
Background: The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, ...
We introduce the ALeRT (Action-dependent Learning Rates with Trends) algorithm that makes two modifications to the learning rate and one change to the exploration rate of traditio...
Maria Cutumisu, Duane Szafron, Michael H. Bowling,...
This paper aims at presenting the application of first-order logic machine learning techniques to two document domains in order to learn rules for recognizing the semantic role of...
Stefano Ferilli, Nicola Di Mauro, Teresa Maria Alt...
We describe an unsupervised system for learning narrative schemas, coherent sequences or sets of events (arrested(POLICE,SUSPECT), convicted( JUDGE, SUSPECT)) whose arguments are ...