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References to publications, sorted by year and author.

Caligiore, D, Cipriani, D, De Marsico, M, Redgrave, P, Triesch, J, and Baldassarre, G (Submitted).
Novelty and surprise intrinsic motivations driving learning of eye movements: an experiments with human adults
Frontiers in Psychology.

Caligiore, D, Parisi, D, and Baldassarre, G (Submitted).
Integrating Reinforcement Learning, Equilibrium Points and Minimum Variance to Understand the Development of Reaching: A Computational Model
Psychological Review.

Campolo, D, Taffoni, F, Schiavone, G, Formica, D, Guglielmelli, E, and Keller, F (Submitted).
Technology for ecological assessment of sensori-motor coordination in infants
International Journal of Social Robotics.

Huelse, M and Lee, M (Submitted).
Coupled sensory-motor map learning

Law, J, Earland, K, Shaw, P, and Lee, M (Submitted).
Robotic modelling of infant reach development
In: IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob 2013).

Law, J, Shaw, P, Lee, M, and Sheldon, M (Submitted).
From Saccades to Play: A model of Coordinated Reaching through Simulated Development on a Humanoid Robot
Transactions on Autonomous Mental Development.

Botvnick, MM, Niv, Y, and A., B (In press).
Hierarchically organized behavior and its neural foundations: A reinforcement-learning perspective

Caballero, J, Lepora, N, and Gurney, K (In preparation).
Bayesian decision making with spike trains
PLoS Computational Biology.

Earland, K, Shaw, P, Law, J, and Lee, M (In preparation).
Overlapping structures in sensorimotor mappings

Gatsoulis, Y and McGinnity, M (In preparation).
Intrinsically Motivated Robots Based on Novelty Detection: Theory and Methods
Frontiers in Neurorobotics.

Gurney, K, Humphries, M, and Redgrave, P (In preparation).
A new framework for cortico-striatal plasticity: behavioural theory meets in vitro data at the reinforcement-action interface
The Journal of Neuroscience.

Law, J, Earland, K, Shaw, P, and Lee, M (In preparation).
Modelling infant reach development with robots
Developmental Science.

Law, J, Shaw, P, Earland, K, Sheldon, M, and Lee, M (In preparation).
A psychology grounded approach for longitudinal development in cognitive robotics
Frontiers in Cognitive Science.

Lewis, J and Gurney, K (In preparation).
A biologically plausible model of sequence generation and action selection
Psychological Review.

Lewis, J, Sheldon, M, and Gurney, K (In preparation).
A multi-scale biomimetic model of intrinsically motivated action schema learning
Frontiers in Cognitive Science.

Mannella, F, Mirolli, M, and Baldassarre, G (In preparation).
Instrumental devaluation may depend on Pavlovian associations between manipulanda and rewards: a computational model
Frontiers in Neuroscience.

Mannella, F, Sperati, V, Shaw, P, Chandrashekhariah, P, Law, M, Lee, J, Triesch, J, Redgrave, P, Gurney, K, Mirolli, M, and Baldassarre, G (In preparation).
A neurorobotic model of the brain systems underlying intrinsically-motivated cumulative learning
Frontiers in Neurorobotics.

Mannella, F, Zappacosta, S, Mirolli, M, and Baldassarre, G (In preparation).
Generalised Spike Time Dependent Plasticity (G-STDP): A computational learning rule capturing multiple brain plasticity processes
Proceedings of the National Academy of Sciences of the United States of America.

Ognibene, D, Pezzulo, G, and Baldassarre, G (In preparation).
Learning and Development of Representations and Attention for Action: A Neurorobotic Study
IEEE Transactions on Autonomous Mental Development.

Santucci, V, Baldassarre, G, and Mirolli, M (In preparation).
Learning multiple skills through competence-based intrinsic motivations: a computational embodied model
Frontiers in Neurorobotics.

Schembri, M, Mirolli, M, and Baldassarre, G (In preparation).
Intrinsic motivations and evolution: a study with a reinforcement-learning simulated robot
Artificial Life.

Siddique, M, McGinnity, M, Condell, J, Gatsoulis, Y, Kerr, E, and Vance, P (In preparation).
A Study on the Co-relationship between Novelty, Intrinsic Motivation and Learning
Frontiers in Psychology/Neurorobotics, Special Issue on Intrinsic motivations and open-ended development in animals, humans, and robots .

Tommasino, P, Caligiore, D, Mirolli, M, and Baldassarre, G (In preparation).
Transfer expert reinforcement learning (TERL): a reinforcement learning architecture that transfers knowledge between skills
Neural Networks.

Castro da Silva, B, Baldassarre, G, Konidaris, G, and Barto, A (2014).
Learning Parameterized Motor Skills on a Humanoid Robot
In: Proceedings of the International Conference on Robotics and Automation (ICRA2014), pp. 1-6.

Eser, J, Zheng, P, and Triesch, J (2014).
Nonlinear Dynamics Analysis of a Self-Organizing Recurrent Neural Network: Chaos Waning
PLoS One.