Abstract
Aim of this work is to study the problem of ensuring safety and effectiveness of a multi-agent robot control system with real-time constraints in the case of learning components usage. Our case study focuses on a robot playing the air hockey game against a human opponent, where the robot has to learn how to minimize opponent’s goals. This case study is paradigmatic since the robot must act in real-time, but, at the same time, it must learn and guarantee that the control system is safe throughout the process. We propose a solution using automata-theoretic formalisms and associated verification tools, showing experimentally that our approach can yield safety without heavily compromising effectiveness.
This research has received funding from the European Community’s Information and Communication Technologies Seventh Framework Programme [FP7/2007-2013] under grant agreement n. [215805], the CHRIS project.
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Metta, G., Natale, L., Pathak, S., Pulina, L., Tacchella, A. (2010). Safe Learning with Real-Time Constraints: A Case Study. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13022-9_14
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DOI: https://doi.org/10.1007/978-3-642-13022-9_14
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