Evolving neural mechanisms for an iterated discrimination task: A robot based model

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3630 LNAI, Issue , 2005, Pages 231-240

  Tuci, Elio ^a   Ampatzis, Christos ^a   Dorigo, Marco ^a  

^a UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER AIDED DESIGN; COMPUTER SIMULATION; DECISION THEORY; HUMAN COMPUTER INTERACTION; NEURAL NETWORKS; ROBOTS;

DISCRIMINATION TASKS; NEURAL MECHANISMS; ROBOT BASED MODELS; SEQUENCE OF TRIALS;

ROBOTICS;

EID: 33645991165     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11553090_24     Document Type: Conference Paper

References (9)

1. C. Ampatzis, E. Tuci, V. Trianni, and M. Dorigo. Evolving communicating agents that integrate information over time: a real robot experiment. Technical Report TR/IRIDIA/2005-12, Université Libre de Bruxelles, 2005.
2. G. Dudek and M. Jenkin. Computational Principles of Mobile Robotics. Cambridge University Press, Cambridge, UK, 2000.
3. D. E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning Addison-Wesley, Reading, MA, 1989.
4. I. Harvey, E. A. Di Paolo, R. Wood, M. Quinn, and E. Tuci. Evolutionary robotics: A new scientific tool for studying cognition. Artificial Life, 11(1-2): 79-98, 2005.
5. P. Husbands, T. Smith, N. Jakobi, and M. O'Shea, Better living through chemistry: Evolving GasNets for robot control. Connection Science, 10(3-4):185-210, 1998.
6. N. Jakobi. Evolutionary robotics and the radical envelope of noise hypothesis: Adaptive Behavior, 6:325-368, 1997.
7. E. A. Di Paolo. Evolving spike-timing dependent plasticity for single-trial learning in robots. Philosophical Transactions of the Royal Society A, 361:2229-2319, 2003.
8. E. Tuci, M. Quinn, and I. Harvey. An evolutionary ecological approach to the study of learning behaviour using a robot-based model. Adaptive Behavior 10(3-4):201-221, 2003.
9. E. Tuci, V. Trianni, and M. Dorigo. 'Feeling' the flow of time through sensory/motor coordination. Connection Science, 16:1-24, 2004.