| Type of Document |
Master's Thesis |
| Author |
Wood, Alexander Burchi, |
| Author's Email Address |
abwood@ncsu.edu |
| URN |
etd-04272005-135341 |
| Title |
Effective Tool Use in a Habile Agent |
| Degree |
Master of Science |
| Graduate Program |
Computer Science |
| Advisory Committee |
| Advisor Name |
Title |
| Robert St. Amant |
Committee Chair |
| Jon Doyle |
Committee Member |
| R. Michael Young |
Committee Member |
|
| Keywords |
- habile
- body schema
- tool use
- MMC
|
| Date of Defense |
2005-03-28 |
| Availability |
unrestricted |
Abstract
Tool use is a hallmark of human intelligence, which has not fully been explored in the artificial intelligence research community. Research in cognitive neuroscience on primates suggests that not only do we maintain a mental representation of our body, but the body schema is modified to include a tool during intentional tool use (Iriki et al., 1996). We have developed a habile (tool-using) agent, based on the Sony Aibo platform, that can pick up a stick and use it as a tool to reach objects previously out of its range. The agent uses a recurrent neural network developed by Steinkühler and Cruse (1998) for maintaining an internal body schema used to find appropriate postures for reaching and grasping tools. We argue that analysis of activities of such tool using agents offers an informative way to evaluate intelligence.
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| Files |
| Filename |
Size |
Approximate Download Time
(Hours:Minutes:Seconds)
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| 28.8 Modem |
56K Modem |
ISDN (64 Kb) |
ISDN (128 Kb) |
Higher-speed Access |
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etd.pdf |
297.77 Kb |
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