Evolution and Development of Neural Controllers for Locomotion, Gradient-Following, and Obstacle-Avoidance in Artificial Insects  

Oleh:

Kodjabachian, J. ; Meyer, J.-A.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 9 no. 5 (1998), page 796-812.
Topik: EVOLUTION; evolution; development; neural controllers; locomotion; gradient; obstacle - avoidance; artificial insects

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.3 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This paper describes how the SGOCE paradigm has been used to evolve developmental programs capable of generating recurrent neural networks that control the behaviour of simulated insects. This paradigm is characterized by an encoding scheme, an evolutionary algorithm, syntactic constraints, and an incremental strategy that are described in turn. The additional use of an insect model equipped with six legs and two antennae made it possible to generate control modules that allowed it to successively add gradient - following and obstacle - avoidance capacities to walking behaviour. The advantages of this evolutionary approach, together with directions for future work, are discussed.

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