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Emergent Effector-Independent Internal Spaces: Adaptation and Intermanual Learning Transfer in Humans and Neural Networks  2007-10-30
International Joint Conference on Neural Networks (IJCNN 2007), 1509-1514.
Hyper-ellipsoidal conditions in XCS  2007-03-13
Butz, M.V., Lanzi, P. L., Wilson, S. W. (2006). Hyper-ellipsoidal conditions in XCS: Rotation, linear approximation, and solution structure. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2006). 1457-1464
Solving Deep Memory POMDPs with Recurrent Policy Gradients  2007-04-17
D. Wierstra, A. Foerster, J. Schmidhuber: Solving Deep Memory POMDPs with Recurrent Policy Gradients. Under review.
Toward an integrated biomimetic model of reaching.   2008-05-15
Caligiore D., Parisi D., Baldassarre G. (2007). Towards an integrated biomimetic model of reaching. Demiris Y., Scassellati B., Mareschal D. (eds.). The 6th IEEE International Conference on Development and Learning (ICDL2007). IEEE Catalog Number: 07EX1740C, ISBN: 1-4244-1116-5, Library of Congress: 2007922394, pp. 241-246. London: Imperial College
Rappresentazioni Anticipatorie: Tre Studi Simulativi   2007-04-15
Giovanni Pezzulo (2006) Proceedings del 3° Convegno Nazionale di Scienze Cognitive (AISC 2006).
Neuroscientists identify brain circuit necessary for memory formation  2017-04-06
New findings challenge standard model of memory consolidation.
Surprise-Driven Belief Revision  2007-04-10
Lorini, E., Castelfranchi, C. (2006); In Proceedings of Second Biennial Conference on Cognitive Science, St. Petersburg, 9-13 June, 2006.
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot  2007-04-17
V. Zhumatiy, F. Gomez, M. Hutter, and J. Schmidhuber: Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot, Proc. of the Int'l Conf. on Intelligent Autonomous Systems, IAS-06, Tokyo, 2006.
A developmental approach to dynamic scene understanding  2007-04-22
Balkenius, C., and Johansson, B. (2006). A developmental approach to dynamic scene understanding. Proceedings of the Sixth International Conference on Epigenetic Robotics (p. 165). Lund University Cognitive Studies, 128.
 

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Anticipatory Cognitive Science is a research field that ensembles artificial intelligence, biology, psychology, neurology, engineering and philosophy in order to build anticipatory cognitive systems that are able to face human tasks with the same anticipatory capabilities and performance. In deep: Cognitive science is the interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience, linguistics, and anthropology. Its intellectual origins are in the mid-1950s when researchers in several fields began to develop theories of mind based on complex representations and computational procedures. Its organizational origins are in the mid-1970s when the Cognitive Science Society was formed and the journal Cognitive Science began. Since then, more than sixty universities in North America, Europe, Asia, and Australia have established cognitive science programs, and many others have instituted courses in cognitive science.