We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
AIRS is an immune-inspired supervised learning algorithm that has been shown to perform competitively on some common datasets. Previous analysis of the algorithm consists almost ex...
– In this paper, we present a hierarchical methodology that learns new walking gaits autonomously while operating in an uncharted environment, such as on the Mars planetary surfa...
Many university classes and commercial training courses rely on classroom lecture and practice exercises to help students learn new skills. The thesis work described in this paper...
In this paper we propose a financial trading system whose strategy is developed by means of an artificial neural network approach based on a recurrent reinforcement learning algo...