Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
New applications for autonomous robots bring them into the human environment where they are to serve as helpful assistants to untrained users in the home or office, or work as ca...
Human-robot interaction is a growing research domain; there are many approaches to robot design, depending on the particular aspects of interaction being focused on. In this paper...
In the framework of an evolutionary approach to machine learning, this paper presents the preliminary version of a learning system that uses Genetic Programming as a tool for autom...
Claudio De Stefano, Antonio Della Cioppa, Angelo M...
Reward shaping is a well-known technique applied to help reinforcement-learning agents converge more quickly to nearoptimal behavior. In this paper, we introduce social reward sha...
Monica Babes, Enrique Munoz de Cote, Michael L. Li...