@conference {3139,
	title = {Cerebellar-Inspired Learning Rule for Gain Adaptation of Feedback Controllers},
	booktitle = {IEEE Mediterranean Conference on Control and Automation},
	year = {2017},
	publisher = {IEEE},
	organization = {IEEE},
	address = {3-6 July 2017 in Valletta, Malta},
	abstract = {<p class="rtejustify">The cerebellum is a crucial brain structure in enabling precise motor control in animals. Recent advances suggest that the timing of the plasticity rule of Purkinje cells, the main cells of the cerebellum, is matched to behavioral function.Simultaneously, counter-factual predictive control (CFPC), a cerebellar-based control scheme, has shown that the optimal rule for learning feed-forward action in an adaptive filter playing the role of the cerebellum must include a forward model of the system controlled. Here we show how the same learning rule obtained in CFPC, which we term as Model-enhanced least mean squares (ME-LMS), emerges in the problem of learning the gains of a feedback controller. To that end, we frame a model-reference adaptive control (MRAC) problem and derive an adaptive control scheme treating the gains of a feedback controller as if they were the weights of an adaptive linear unit. Our results demonstrate that the approach of controlling plasticity with a forward model of the subsystem controlled can provide a solution to a wide set of adaptive control problems</p>
},
	author = {I. Herreros and X. D. Arsiwalla and C. Della Santina and J.-Y. Puigbo and A. Bicchi and P. F. M. J. Verschure}
}
@conference {2226,
	title = {XIM-Engine: a software framework to support the development of interactive applications that uses conscious and unconscious reactions in immersive mixed reality},
	booktitle = {VIRTUAL REALITY INTERNATIONAL CONFERENCE},
	year = {2014},
	abstract = {<p>The development of systems that allow multimodal interpretation of human-machine interaction is crucial to advance our understanding and validation of theoretical models of user behavior. In particular, a system capable of collecting, perceiving and interpreting unconscious behavior can provide rich contextual information for an interactive system. One possible application for such a system is in the exploration of complex data through immersion, where massive amounts of data are generated every day both by humans and computer processes that digitize information at different scales and resolutions thus exceeding our processing capacity. We need tools that accelerate our understanding and generation of hypotheses over the datasets, guide our searches and prevent data overload. We describe XIM- engine, a bio-inspired software framework designed to capture and analyze multi-modal human behavior in an immersive environment. The framework allows performing studies that can advance our understanding on the use of conscious and unconscious reactions in interactive systems.</p>
},
	author = {P. Omedas and A. Betella and Zucca, R. and X. D. Arsiwalla and Pacheco, D. and J. Wagner and F. Lingenfelser and D. Mazzei and A Lanata and A. Tognetti and Goldhoorn, A. and Guerra, E. and Alqu{\`\i}zar, R. and Grau, A. and Sanfeliu, A. and D. De Rossi and E. Andr{\'e} and P. F. M. J. Verschure}
}
@conference {1812,
	title = {Advanced Interfaces to Stem the Data Deluge in Mixed Reality: Placing Human (un)consciuosness in the Loop},
	booktitle = {ACM SIGGRAPH 2013},
	year = {2013},
	address = {New York, NY, USA},
	keywords = {Bioengineering},
	url = {10.1145/2503385.2503460},
	author = {A. Betella and E. Mart{\`\i}nez and R. Zucca and X. D. Arsiwalla and P Omedas and S. Wierenga and A. Mura and J. Wagner and F. Lingenfelser and E. Andr{\'e} and D. Mazzei and A. Tognetti and A Lanata and D. De Rossi and P. F. M. J. Verschure}
}
@conference {1998,
	title = {A Sensing Architecture for Empathetic Data Systems},
	booktitle = {ACM International Conference Proceeding Series},
	year = {2013},
	month = {7-8 March},
	pages = {{\textendash}},
	publisher = {ACM Digital Library},
	organization = {ACM Digital Library},
	doi = {10.1145/2459236.2459253},
	url = {http://dx.medra.org/10.1145/2459236.2459253},
	author = {J. Wagner and F. Lingenfelser and E. Andr{\'e} and D. Mazzei and A. Tognetti and D. De Rossi and A. Betella and R. Zucca and P Omedas and P. F. M. J. Verschure}
}
