Welcome to my site!
Saturday, 12 June 2004

ImageThis is the website of Ricardo Sanz, professor in systems engineering and automatic control and researcher in the field of autonomous systems.

In this site you will find information regarding my activitiy as well as other sources that may be of interest to you. Feel free to explore the site and to suggest any improvement to it.

I do most of my activity as part of the Autonomous Systems Laboratory. ASLab is a research group of ample interests ranging from conventional control and real-time systems to model-based engineering processes and artificial intelligence.

This last is, indeed, my main topic of interest; or to be more precise, I'm interested in mind theory, both artificial and natural within the long term engineering objective of systematically creating better machines by means of improving their intelligence.

Last Updated ( Saturday, 08 July 2017 )
It has always been models
Sunday, 30 July 2017
There is a relatively recent boom on model-based X. Model-based development, model-based design, model-based systems engineering, ...

In all the domains of engineering, it looks like we have just discovered the use of models to support our work. But this is, obviously, false. It has always been models. All around. All the time.

Last Updated ( Sunday, 30 July 2017 )
Ontologies as Backbone of Cognitive Systems Engineering
Friday, 10 March 2017
Ricardo Sanz, Julita Bermejo, Juan Morago and Carlos Hernández
INCOSE Cognition And OntologieS (CAOS) 2017

Cognitive systems are starting to be deployed as appliances across the technological landscape of modern societies. The increasing availability of high performance computing platforms has opened an opportunity for statistics-based cognitive systems that per- form quite as humans in certain tasks that resisted the symbolic methods of classic artificial intelligence. Cognitive artefacts appear every day in the media, raising a wave of mild fear concerning artificial intelligence and its impact on society. These systems, performance notwithstanding, are quite brittle and their reduced dependability limits their potential for massive deployment in mission-critical applications —e.g. in autonomous driving or medical diagnosis. In this paper we explore the actual possibility of building cognitive systems using engineering-grade methods that can assure the satisfaction of strict requirements for their operation. The final conclusion will be that, besides the potential improvement provided by a rigorous engineering process, we are still in need of a solid theory —possibly the main outcome of cognitive science— that could sustain such endeavour. In this sense, we propose the use of formal ontologies as back- bones of cognitive systems engineering processes and workflows.

Ontologies as Backbone of Cognitive Systems Engineering. Ricardo Sanz, Julita Bermejo, Juan Morago and Carlos Hernández. AISB Symposium on Cognition And OntologieS (CAOS) 2017

Draft paper @ ASLab

Last Updated ( Saturday, 11 March 2017 )
Emotions and the engineering of adaptiveness in complex systems
Thursday, 11 April 2013
M.G. Sánchez-Escribano & R. Sanz
INCOSE Conference on Systems Engineering Research (CSER 2014)

A major challenge when building complex and critical systems is the management of change in the system and in its operational environment. The increasing complexity forces autonomous systems to detect critical changes to avoid their progress towards undesirable states. We need new methods to build systems that can tune their adaptability protocols, transferring the control of uncertainty to their inner domain to strive for wellness. In essence, these are mechanisms to impose the fulfillment of system-wide wellness requirements to reduce the influence of the outer domain to be fully driven by the influence of the inner one. From the stance of cognitive systems, biological emotion suggests a strategy to configure value-based systems to use semantic self-representations of the state. A method inspired by emotion theories can causally connect the inner domain of the system and its objectives of wellness, focusing on dynamically adapting the system to avoid the progress of critical states. This method shall endow the system with a transversal mechanism to monitor its inner processes, detecting critical states and managing its adaptivity in order to maintain the wellness goals. The paper describes the current vision produced by this work-in-progress.

Emotions and the engineering of adaptiveness in complex systems. M.G. sanchez-Escribano & R. Sanz. INCOSE Conference on Systems Engineering Research (CSER 2014)

Draft paper @ ASLab

Last Updated ( Saturday, 25 January 2014 )
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