In this paper we propose a model for human learning and decision making in environments of repeated Cliff-Edge (CE) interactions. In CE environments, which include common daily in...
Human-robot interaction has been identified as one of the major open research directions in mobile robotics. This paper considers a specific type of interaction: short-term and sp...
Jamieson Schulte, Charles R. Rosenberg, Sebastian ...
We present a method for learning a human understandable, executable model of an agent's behavior using observations of its interaction with the environment. By executable we ...
Andrew Guillory, Hai Nguyen, Tucker R. Balch, Char...
This paper describes a novel method by which a dialogue agent can learn to choose an optimal dialogue strategy. While it is widely agreed that dialogue strategies should be formul...
Marilyn A. Walker, Jeanne Frommer, Shrikanth Naray...
One of the key issues in reasoning with multiple interacting intelligent agents is how to model and code the decision making process of the agents. In Artificial Intelligence (AI...