XPERO: Learning by experimentation

Data inizio
1 aprile 2006
Durata (mesi) 
Informatica, Ingegneria per la medicina di innovazione
Responsabili (o referenti locali)
Fiorini Paolo
Parole chiave
robotics, machine learning, artifical intelligence

The overall objective of the proposed project is to develop an embodied cognitive system, which is
able to conduct experiments in the real world with the purpose of gaining new insights about the
world and the objects therein and to develop and improve its own cognitive skills and overall
performance. It is obvious that for the ability to conduct experiments in the real world, embodiment is
a fundamental prerequisite.
Expected results of the project are basic models, techniques, and system solutions, enabling an
embodied agent to autonomously design and conduct experiments in a given context - stimulating the
agent's desire to gather new knowledge - and to extract new insights from the results of the
XPERO proposes to approach this problem by developing a methodology for learning by
experimentation. Enabling an embodied agent, in the sequel called robot, to design and conduct
experiments in a natural real world setting and to extract new insights is more than just adding
another feature to a technical system. The ability to conduct experiments in the real world and extract
new knowledge and insights pushes open the door to a new quality of embodied systems namely to
potentially unlimited autonomous learning. This ability enables the robot to grow in an unlimited
fashion its cognitive capacity and its performance to accomplish meaningful tasks in the real world.
Limitations are only set by the surrounding world and its own physical capabilities, and not by
availability of a programmer, teacher or learning material.
We plan to achieve this objective by performing research and development in the following areas
Stimulation of Experiment, Design and Execution of Experiments, Observation and Evaluation of
Experiments, Representing Knowledge and Gaining Insights and Engineering the Experimental Loop.
By integrating the results of the research in these areas in demonstrations of increasing complexity
and performing regular dissemination activities, we will contribute to expand the state of the art of
machine learning and embodied cognitive systems and disseminate

Enti finanziatori:

Unione Europea
Finanziamento: assegnato e gestito dal Dipartimento
Programma: EUROPA - Progetti Europei

Partecipanti al progetto

Federico Di Palma
Paolo Fiorini
Incaricato alla ricerca
Stefano Galvan
Lorenzo Grespan
Monica Reggiani
Aree di ricerca coinvolte dal progetto
Sistemi ciberfisici
Embedded and cyber-physical systems