Evolving a Neural Model of Insect Path Integration  

Oleh:

Haferlach, Thomas ; Wessnitzer, Jan ; Mangan, Michael ; Webb, Barbara

Jenis: Article from Journal - e-Journal
Dalam koleksi: Adaptive Behavior vol. 15 no. 3 (Sep. 2007), page 273–287.
Topik: path integration; direction cells; genetic algorithm; neural network; simulation; robot
Fulltext: 273.pdf (714.4KB)

Isi artikel

Path integration is an important navigation strategy in many animal species. We use a genetic algorithm to evolve a novel neural model of path integration, based on input from cells that encode the heading of the agent in a manner comparable to the polarization-sensitive interneurons found in insects. The home vector is encoded as a population code across a circular array of cells that integrate this input. This code can be used to control return to the home position. We demonstrate the capabilities of the network under noisy conditions in simulation and on a robot.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali