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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaolin Hu Ou Li |
| Copyright Year | 2006 |
| Description | Author affiliation: Comput. Sci. Dept., Georgia State Univ., Atlanta, GA (Xiaolin Hu; Ou Li) |
| Abstract | One mechanism for an intelligent agent to adapt to substantial environmental changes is to change the structure of its behavior network. In earlier work, we developed a context-dependent behavior selection architecture that uses structure change as the main mechanism to generate different behavior patterns according to different behavioral contexts. This paper investigates how the structure of such a behavior network can be learned. We present a structure learning method based on generic algorithm (GA). The results show that given a particular dynamic environment, consistent and robust structure can be learned to allow an agent to behave adaptively. |
| Starting Page | 407 |
| Ending Page | 410 |
| File Size | 226210 |
| Page Count | 4 |
| File Format | |
| ISBN | 0769527485 |
| DOI | 10.1109/IAT.2006.115 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-12-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Intelligent agent Intelligent systems Computer science Computer architecture Learning systems Robustness Animal behavior Context modeling Switches |
| Content Type | Text |
| Resource Type | Article |
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