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Alergic Talks Wed Nov 7th

Page history last edited by PBworks 16 years, 8 months ago

Alergic Double-bill -- Wed 7th Nov, 4:30pm in ARUN-401

Two presentations from ECAL 2007 in Lisbon, brought all the way to Sussex.

Each about 20/30 mins plus time for questions.

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(A)

New Models for Old Questions: Evolutionary Robotics and the 'A not B' error.

Rachel Wood, Ezequiel Di Paolo

Abstract. In psychology the 'A not B' error, whereby infants perse-

verate in reaching to the location where a toy was previously hidden

after it has been moved to a new location, has been the subject of fifty

years research since it was first identified by Piaget [1]. This paper de-

scribes a novel implementation of the 'A not B' error paradigm which

is used to test the notion that minimal systems evolutionary robotics

modelling can be used to explore developmental process and to generate

new hypotheses for test in natural experimental populations. The model

demonstrates that agents controlled by plastic continuous time recurrent

neural networks can perform the 'A not B' task and that homeostatic

mediation of plasticity can produce perseverative error patterns similar

to those observed in human infants. In addition, the model shows a

developmental trend for the production of perseverative errors to reduce

during development.

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(B)

Evolution of Neural Networks for Active Control of Tethered Airfoils

Allister Furey, Inman Harvey

Abstract. Recent development in tethered airfoil i.e. kite technology allows the

possibility of exploitation of wind energy at higher altitudes than achievable

with traditional wind turbines, with greater efficiency and reduced costs. This

study describes the use of evolutionary robotics techniques to build

neurocontrollers that maximize energy recoverable from wind by kite control

systems in simulation. From initially randomized starting conditions,

neurocontrollers rapidly develop under evolutionary pressure to fly the kite in

figure eight trajectories that have previously been shown to be an optimal path

for power generation. Advantages of this approach are discussed and data is

presented which demonstrates the robustness of trajectory control to

environmental perturbation.
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