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Combining Gradient-Based With Evolutionary Online Learning: An Introduction to Learning Classifier Systems
Seventh International Conference on Hybrid Intelligent Systems (HIS 2007), 12-17.
Improving the performance of Pittsburgh learning classifier systems using a default rule
(2007). In Kovacs, T. et al. (Eds.) Learning Classifier Systems: International Workshops, IWLCS 2003-2005, LNAI 4399, Springer-Verlag, Berlin Heidelberg. ...
Combining Gradient-Based With Evolutionary Online Learning: An Introduction to Learning Classifier Systems
Seventh International Conference on Hybrid Intelligent Systems (HIS 2007), 12-17.
A reinforcement-learning model of top-down attention based on a potential-action map
Ognibene, D.; Balkenius, C. & Baldassarre, G.. 2008. A reinforcement-learning model of top-down attention based on a potential-action map. Pezzulo Giovanni, ...
Agents with Anticipatory Behaviors: To be Cautious in a Risky Environment
Cristiano Castelfranchi and Rino Falcone and Michele Piunti, European Conference Articial Intelligence (ECAI06) pp. 693-694
Integrating Reinforcement-Learning, Accumulator Models, and Motor-Primitives to Study Action Selection and Reaching in Monkeys
Ognibene, D. and Mannella, F. and Pezzulo, G. and Baldassarre, G. Proceedings of ICCM 2006
A Model of Reaching That Integrates Reinforcement Learning and Population Encoding of Postures
Ognibene, Dimitri and Rega, Angelo and Baldassarre, Gianluca From Animals to Animats 9, 9th International Conference on Simulation of Adaptive Behavior, SAB ...
Apprendimento per rinforzo e codifica tramite popolazione neurale: un modello per il reaching applicato a due task
WIVA3 - 3° Workshop Italiano Vita Artificiale
Building Robots with Analogy-Based Anticipation
Petkov, G., Naydenov, Ch., Grinberg, M., Kokinov(2006); Proceedings of the KI 2006, 29th German Conference on Artificial Intelligence, Bremen
Surprise-Driven Belief Revision
Lorini, E., Castelfranchi, C. (2006); In Proceedings of Second Biennial Conference on Cognitive Science, St. Petersburg, 9-13 June, 2006.
Schema-based design and the AKIRA Schema Language
Pezzulo, G. & Calvi, G. Schema-based design and the AKIRA Schema Language: An Overview Anticipatory Behavior. In Butz, M.; Sigaud, O.; Pezzulo, G. & ...
Quasi-Online Reinforcement Learning for Robots
B. Bakker, V. Zhumatiy, G. Gruener, J. Schmidhuber: Quasi-Online Reinforcement Learning for Robots, IEEE International Conference on Robotics and Automation ...
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot
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. ...
Holonomic Control of a robot with an omnidirectional drive
R. Rojas, A. Gloye Förster: Holonomic Control of a robot with an omnidirectional drive, KI - Künstliche Intelligenz, vol. 20, nr. 2, BöttcherIT Verlag, ...
Training Recurrent Neural Networks by Evolino
J. Schmidhuber, D. Wierstra, M. Gagliolo, F. Gomez: Training Recurrent Neural Networks by Evolino. To appear in Neural Computation.
Shared Intention Revisited: The Limits of Egoism are Not the Limits of Individualism
Tummolini, L. (submitted to Economics and Philosophy)
The cognitive structure of Surprise: looking for basic principles
Lorini, E., Castelfranchi, C. (2007); To appear in Topoi: An International Review of Philosophy, 26(1).
Toward an integrated biomimetic model of reaching.
Caligiore D., Parisi D., Baldassarre G. (2007). Towards an integrated biomimetic model of reaching. Demiris Y., Scassellati B., Mareschal D. (eds.). The 6th ...
mindracesfile.2008-05-15.5554692676
Trajectory learning through motor babbling: reaching with obstacle avoidance.
Ferrauto Tomassino, Ognibene Dimitri, Caligiore Daniele, Baldassare Gianluca (2007). Trajectory learning through motor babbling: reaching with obstacle ...
ZMINDRACESFILE_INDEXING_DOCUMENT
Zmindracesfile_indexing_document This is a special MindRACES file used to create categories indexes for the others
A Schema Based Model of the Praying Mantis
(2006) From animals to animats 9: Proceedings of the Ninth International Conference on Simulation of Adaptive Behaviour
The unexpected aspects of Surprise
Lorini, E., Castelfranchi, C. (2006); International Journal of Pattern Recognition and Artificial Intelligence, 20 (6), pp. 817-835.
Using motor babbling and Hebb rules for modeling the development of reaching with obstacles and grasping
Caligiore D., Ferrauto T., Parisi D., Accornero N., Capozza M., Baldassarre G. (2008). Using motor babbling and Hebb rules for modeling the development of ...
Integrating Epistemic Action (Active Vision) and Pragmatic Action (Reaching): A Neural Architecture for Camera-Arm Robots.
Ognibene, D.; Balkenius, C. & Baldassarre, G.. 2008. Integrating Epistemic Action (Active Vision) and Pragmatic Action (Reaching): A Neural Architecture for ...
DiPRA Distributed Practical Reasoning Architecture
(2007) Proceedings of IJCAI 2007
A testbed for neural-network models capable of integrating information in time.
Zappacosta S., Nolfi S., Baldassarre G. (in press). A testbed for neural-network models capable of integrating information in time. In Butz M., Sigaud O., ...
Brains,anticipations, individual and social behavior: an introduction to anticipatory behavior systems.
Butz M., Sigaud O., Pezzulo G., Baldassarre G. (in press). Brains, anticipations, individual and social behavior: an introduction to anticipatory behavior ...
Learning to select targets within targets in reaching tasks.
Herbort O., Ognibene O., Butz M.V., Baldassarre G. (2007). Learning to select targets within targets in reaching tasks. The 6th IEEE International Conference ...
RNN-based Learning of Compact Maps for Efficient Robot Localization
A. Foerster, A. Graves, J. Schmidhuber: RNN-based Learning of Compact Maps for Efficient Robot Localization. ESANN 2007.
 

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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.