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| Content Provider | Springer Nature Link |
|---|---|
| Author | Suzuki, Reiji Arita, Takaya |
| Copyright Year | 2013 |
| Abstract | Niche construction is a process whereby organisms, through their metabolism, activities, and choices, modify their own and/or each other’s niches. Our purpose is to clarify the interactions between evolution and niche construction by focusing on non-linear interactions between genetic and environmental factors shared by interacting species. We constructed a new fitness landscape model termed the NKES model by introducing environmental factors and their interactions with genetic factors into Kauffman’s NKCS model. The evolutionary experiments were conducted using hill-climbing and niche-constructing processes on this landscape. The results have shown that the average fitness among species strongly depends on the ruggedness of the fitness landscape (K) and the degree of the effect of niche construction on genetic factors (E). Especially, we observed two different roles of niche construction: moderate perturbations on hill-climbing processes on the rugged landscapes, and the strong constraint which yields the convergence to a stable state. Also, we show that the difference in the structures of (direct or indirect) interactions among species drastically changes the coevolutionary process of the whole ecosystem by comparing the evolutionary dynamics of the NKES model with that of the NKCS model. |
| Starting Page | 144 |
| Ending Page | 151 |
| Page Count | 8 |
| File Format | |
| ISSN | 14335298 |
| Journal | Artificial Life and Robotics |
| Volume Number | 18 |
| Issue Number | 3-4 |
| e-ISSN | 16147456 |
| Language | English |
| Publisher | Springer Japan |
| Publisher Date | 2013-10-22 |
| Publisher Place | Tokyo |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Niche construction Coevolution Fitness landscape NKCS model 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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