Actively Adaptive Agent for Human-Agent Collaborative Task

Authors:
Yong Xu;Yoshimasa Ohmoto;Kazuhiro Ueda;Takanori Komatsu;Takeshi Okadome;Koji Kamei;Shogo Okada;Yasuyuki Sumi;Toyoaki Nishida
Affiliations:
Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto, Japan 606-8501;Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto, Japan 606-8501;Department of System Sciences, the University of Tokyo,;International Young Researcher Empowement Center, Shinshu University,;School of Technology and Science, Kwansei Gakuin University,;Innovative Communication Laboratory, NTT Communication Science Laboratories,;Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto, Japan 606-8501;Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto, Japan 606-8501;Department of Intelligence Science and Technology, Graduate School of Informatics, Kyoto University, Kyoto, Japan 606-8501
Venue:
AMT '09 Proceedings of the 5th International Conference on Active Media Technology
Year:
2009

Citing 5
Cited 0

Autonomous interface agents

Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Teachable robots: Understanding human teaching behavior to build more effective robot learners

Artificial Intelligence
WOZ experiments for understanding mutual adaptation

AI & Society - Special Issue: Social intelligence design: a junction between engineering and social sciences
A Platform System for Developing a Collaborative Mutually Adaptive Agent

IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Modeling adaptive autonomous agents

Artificial Life

Quantified Score

Hi-index	0.00

Visualization

Abstract

Active interface is one of critical characteristics of agents who have to interact with human users to achieve human-agent collaboration. This characteristic is especially important in beginning phase of human-agent interaction when an ordinary human user begins to interact with an adaptive autonomous agent. In order to investigate principal characteristics of an active interface, we developed a human-agent collaborative experimental environment named WAITER. Two types of experiment: WOZ agent experiment and autonomous agent experiment were conducted. Objective of the experiment is to observe how human users change their instructions when interacting with adaptive agents with different degree of freedom. Experimental results indicate that participants can recognize changes of agent's actions and change their instruction methods accordingly. It infers that changes of instruction method depend not only on waiter agent's reactions, but also on human manager's cognitive models of the agent.