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| Content Provider | Springer Nature Link |
|---|---|
| Author | Nakamura, Keita |
| Copyright Year | 2015 |
| Abstract | This study proposes a method to acquire adaptive behavior for artificial creature which has a lot of joints using a combined Artificial Neural Network (ANN). Experiment in this study focuses on artificial fish model, which has a lot of joints, tracking towards a target in the virtual water environment. In order to control motions of joints, a combined ANN is implemented with the model. At first, one ANN is prepared to control specific joints so as to swim basically in response to minimal input information using evolutionary computation in preliminary experiments. And an new network is constructed by combining its network and the other network. In order to acquire complicate behavior for artificial creature, weights of combined ANN are optimized. Experiment result shows the model which has many joints acquire adaptive swimming behavior towards a target by optimizing combined network. |
| Starting Page | 91 |
| Ending Page | 97 |
| Page Count | 7 |
| File Format | |
| ISSN | 14335298 |
| Journal | Artificial Life and Robotics |
| Volume Number | 21 |
| Issue Number | 1 |
| e-ISSN | 16147456 |
| Language | English |
| Publisher | Springer Japan |
| Publisher Date | 2015-12-31 |
| Publisher Place | Tokyo |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Artificial life Evolutionary computations Learning Neural networks Artificial Intelligence (incl. Robotics) Computation by Abstract Devices Control, Robotics, Mechatronics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Biochemistry, Genetics and Molecular Biology |
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