2007 Fiscal Year Final Research Report Summary
Acquisition of Word-meaning and Dialogue Strategies Aiming at the Communication in a Symbiotic Society of Human and Agents
| Project/Area Number |
18500130
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Perception information processing/Intelligent robotics
|
|---|
| Research Institution | Toyohashi University of Technology |
|---|
Principal Investigator |
NITTA Tsuneo Toyohashi University of Technology, Graduate School of Engineering, Professor (70314101)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
KATSURADA Kouichi Toyohashi University of Technology, Graduate School of Engineering, lecturer (80324490)
IRIBE Yurie Toyohashi University of Technology, Information and Media Center, Assistant Professor (40397500)
|
|---|
| Project Period (FY) |
2006 – 2007
|
| Keywords | Symbiosis of human and agents / Communication / Dialogue strategies / Word meaning acquisition / Learning biases / Reinforcement learning |
|---|
| Research Abstract |
The symbiotic society of human and agents that enables them real interaction in the near future is expected. To accelerate related studies, facilities of spoken dialogue interaction and development tools are very important. We have studied first: (a) word-meaning acquisition of image objects, (b) dialogue strategy acquisition for the agents.
In the word-meaning acquisition, we propose a method based on an Online-EM algorithm that enables agents to find out the features of objects represented by spoken words, however, the algorithm needs a lot of examples to determine the word-meaning, or correct distributions. To overcome the problem, we have applied two types of learning biases, shape bias and mutual exclusivity bias, observed in children's language development. Experimental results showed that the improved method with biases could efficiently acquire word meanings.
In the dialogue strategy acquisition, we propose a Q-learning based algorithm in which agents acquire different strategies according with their roles, asking or teaching, by estimating counterpart's comprehension level from its facial expression and utterance. Experimental results showed the effectiveness of both strategies of teaching and asking. We have also developed a tool with the abovementioned functionalities of word-meaning acquisition and dialogue strategy acquisition. The experimental results on cooperative works showed the effectiveness of acquired action strategies to complete tasks quickly.
|
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
[Presentation] 「研究成果報告書概要(欧文)」より2008
Author(s)
Yuta Mizoguchi, Ryo Taguchi, Masashi Kimura, Tomoya Doioka, Kouichi Katsurada, Tsuneo Nitta
Organizer
The 22^<nd> Annual Conference of the Japanese Society for Artificial Intelligence (3E3-08)
Year and Date
20080000
-
-
-
-
-
