| Cliff, D. and Grand, S. The Creatures Global Digital Ecosystem. Artificial Life, 5. 77-94. |
....it is worth mentioning that there is no wall avoidance strategy implemented yet (it constitutes one of our future research steps) A. Neural Controller Neural networks appear to be the most promising means of emerging adaptive behaviors in complex multi agent environments, as stressed in [4] [5] and [6] Therefore, a feedforward neural controller is employed to manage the agents motion and is described in this subsection. Apart from the neural controller, an Artificial Potential Field employed for controlling the agents movement is also introduced in Subsection II B. 1) Input: Using ....
....used can be described as follows. Each Human has a genome that encodes the connection weights of its neural network. A population of 20 (we keep this number low because of the increasing computational cost) neural networks (Humans) is initialized randomly while initial real values that lie within [ 5, 5] for their connection weights are picked randomly from a uniform distribution. Then, at each time step: 1) Every Human in the population is cloned 20 times. These 20 clones are placed in the FlatLand environment and tested for an evaluation period (e.g. 200 simulation steps) The outcome of this ....
D. Cliff and S. Grand, "The creatures global digital ecosystem," Artificial Life, vol. 5, pp. 77--94, 1999.
No context found.
Cliff, D. and Grand, S. The Creatures Global Digital Ecosystem. Artificial Life, 5. 77-94.
No context found.
Cliff, D. and Grand, S. The Creatures Global Digital Ecosystem. Artificial Life, 5. 77-94.
No context found.
D. Cliff and S. Grand. The creatures global digital ecosystem. Artificial Life, 5:77--94, 1999.
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