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List of all publications whose research was partially or wholly funded by the IM-CLeVeR project, ordered by year and then by author.

This folder holds the following references to publications, sorted by year and author.

There are 323 references in this bibliography folder.

Ngo, H, Luciw, M, Anh Vien, N, and Schmidhuber, J (2013).
Upper Confidence Weighted Learning for Efficient Exploration in Multiclass Prediction with Binary Feedback
In: International Joint Conference on Artificial Intelligence (IJCAI 2013).

Ngo, H, Luciw, M, Ngo, A, and Schmidhuber, J (2013).
Efficient exploration for accelerating human-robot interactive learning in multiclass prediction with partial feedback
In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-13).

Nichols, E, McDaid, L, and Siddique, N (2013).
Biologically Inspired SNN for Robot Control
In: IEEE Transactions on Cybernetics, vol. 43, pp. 115 - 128.

Ognibene, D, Catenacci Volpe, N, Pezzulo, G, and Baldassarre, G (2013).
Learning epistemic actions in model-free memory-free reinforcement learning: experiments with a neuro-robotic model
In: Second International Conference on Biomimetic and Biohybrid Systems. Proceedings , ed. by N. F. Lepora, A. Mura, H. G. Krapp, P. F. M. J. Verschure, T. J. Prescott, pp. 191-203, Berlin, Springer. Lecture Notes in Computer Science, vol. 8064.

O’Flynn, B, Connolly, J, Condell, J, Curran, K, and Gardiner, P (2013).
Novel Smart Sensor Glove for Arthritis Rehabilitation
In: Body Sensor Networks Conference.

O’Flynn, B, Sanchez, JT, Angove, P, Connolly, J, Condell, J, and Curran, K (2013).
Wireless Smart Glove for arthritis rehabilitation
In: Smart Systems Integration conference.

Pamplona, D, Triesch, J, and Rothkopf, C (2013).
Eye's imaging process explains ganglion cells anisotropies
In: Proceedings of Computational and Systems Neuroscience (Cosyne 13).

Pengsheng, Z, Dimitrakakis, C, and Triesch, J (2013).
Network self-organization explains the statistics and dynamics of synaptic connection strengths in cortex
PLoS computational biology, 9(1):e1002848.

Polizzi di Sorrentino, E, Sabbatini, G, Truppa, V, Bordonali, A, Baldassarre, G, and Visalberghi, E (2013).
Action-outcome contingencies affect spontaneous exploration and learning in capuchin monkeys
In: Proceedings of the XXI Congress of the Italian Primatological Association.

Redgrave, P, Gurney, K, Stafford, T, Thirkettle, M, and Lewis, J (2013).
The role of the basal ganglia in discovering novel actions
In: Intrinsically Motivated Learning in Natural and Artificial Systems, ed. by Baldassarre Gianluca and Mirolli Marco, pp. 129-150, Springer-Verlag, Berlin.

Rothkopf, C and Ballard, D (2013).
Modular inverse reinforcement learning for visuomotor behavior
Biological Cybernetics, 107(4):477-490.

Rothkopf, C and Ballard, D (2013).
Learning to coordinate repertoirs of behaviors: credit assignment and module activation
In: Computational and Robotic Models of the Hierarchical Organization of Behavior, ed. by Baldassarre, G., Mirolli, M., Springer.

Santucci, V, Baldassarre, G, and Mirolli, M (2013).
Intrinsic motivation signals for driving the acquisition of multiple tasks: a simulated robotic study
In: Proceedings of the 12th International Conference on Cognitive Modelling (ICCM2013), ed. by West Robert and Stewart Terry, pp. 59-64.

Santucci, VG, Baldassarre, G, and Mirolli, M (2013).
Which is the best intrinsic motivation signal for learning multiple skills?
Frontiers in Neurorobotics, 7:e1-14.

Schmidhuber, J (2013).
Maximizing Fun By Creating Data With Easily Reducible Subjective Complexity
In: Intrinsically Motivated Learning in Natural and Artificial Systems, ed. by Baldassarre, G., Mirolli, M., pp. 95-128, Springer, Berlin.

Schmidhuber, J (2013).
PowerPlay: training an increasingly general problem solver by continually searching for the simplest still unsolvable problem
Front. Psychol., 4(313).

Seepanomwan, K, Caligiore, D, Baldassarre, G, and Cangelosi, A (2013).
A cognitive robotic model for mental rotation
In: Proceedings of the 2013 IEEE Symposium Series on Computational Intelligence, ed. by Suganthan P. N., Fogel David B., Fogel Gary B., Ishibuchi Hisao, Sundaram Suresh, Kozma Robert and Das Swagatam, pp. e1-8, Piscataway, NJ, IEEE.

Seepanomwan, K, Caligiore, D, Baldassarre, G, and Cangelosi, A (2013).
Modeling Mental Rotation in Cognitive Robots
Adaptive Behaviour.

Shah, A, Barto, A, and Fagg, A (2013).
A Dual Process Account of Coarticulation in Motor Skill Acquisition
Journal of Motor Behavior, 45:531--549.

Shaw, P, Law, J, and Lee, M (2013).
An evaluation of environmental constraints for biologically constrained development of gaze control on an iCub robot
PALADYN Journal of Behavioral Robotics, 3(3):147-155.

Srivastava, R, Steunebrink, B, and Schmidhuber, J (2013).
First experiments with PowerPlay
In: Neural Networks.

Stafford, T, Walton, T, Hetherington, L, Thirkettle, M, Gurney, K, and Redgrave, P (2013).
A novel behavioural task for researching intrinsic motivations
In: Intrinsically Motivated Learning in Natural and Artificial Systems, ed. by Baldassarre Gianluca and Mirolli Marco, pp. 395-410, Springer-Verlag, Berlin.

Thill, S, Caligiore, D, Borghi, A, Ziemke, T, and Baldassarre, G (2013).
Theories and computational models of affordance and mirror systems: An integrative review
Neuroscience and Biobehavioral Reviews, 37:491-521.

Thirkettle, M, Walton, T, Shah, A, Gurney, K, Redgrave, P, and Stafford, T (2013).
The path to learning: Action acquisition is impaired when visual reinforcement signals must first access cortex
Behavioural Brain Research, 243:267--272.

Trapanese, C, Sabbatini, G, Manrique, H, De Bortoli Vizioli, A, Call, J, and Visalberghi, E (2013).
Do capuchin monkeys use tools with different properties in the correct sequence?
In: Proceedings of the XXI Congress of the Italian Primatological Association.