A comparative study of reinforcement learning techniques on dialogue management
EACL '12 Proceedings of the Student Research Workshop at the 13th Conference of the European Chapter of the Association for Computational Linguistics
Online Complex Action Learning and User State Estimation for Adaptive Dialogue Systems
ICTAI '12 Proceedings of the 2012 IEEE 24th International Conference on Tools with Artificial Intelligence - Volume 01
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In this paper, we present a system targeted for assistive living environments, that is able to control the actuators of a robot and manipulate objects that lie on a table. An adaptive dialogue system is responsible for interacting with the user, retrieving his/her intentions and reacting accordingly. Our system is able to learn in real time how to solve complicated tasks by combining solutions to simpler ones, thus reusing previous knowledge. It is also able to effectively plan and execute table top object manipulation, which can have a great impact in the quality of life of an elderly, disabled or injured person.