Evolving Neural Mechanisms for an Iterated Discrimination Task: A Robot Based Model
This paper is about the design of an artificial neural network to control an autonomous robot that is required to iteratively solve a discrimination task based on time-dependent structures. The “decision making” aspect demands the robot “to decide”, during a sequence of trials, whether or not the type of environment it encounters allows it to reach a light bulb located at the centre of a simulated world. Contrary to other similar studies, in this work the robot employs environmental structures to iteratively make its choice, without previous experience disrupting the functionality of its decision-making mechanisms.
KeywordsDiscrimination Task Light Bulb Autonomous Robot Dark Zone Robot Controller
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- 1.Ampatzis, C., Tuci, E., Trianni, V., Dorigo, M.: Evolving communicating agents that integrate information over time: a real robot experiment. Technical Report TR/IRIDIA/2005-12, Université Libre de Bruxelles (2005)Google Scholar
- 8.Tuci, E., Quinn, M., Harvey, I.: An evolutionary ecological approach to the study of learning behaviour using a robot-based model. Adaptive Behavior 10(3-4), 201–221 (2003)Google Scholar