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Optimal Actuation Strategies for Sensor/Actuator Networks

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3 Author(s)
F. Thouin ; McGill University, Department of Electrical and Computer Engineering, 3480 University, Montreal, Quebec, Canada H3A 2A7. Email: fthoui@ece.mcgill.ca ; R. Thommes ; M. J. Coates

Wireless sensor-actuator networks (SANETs), in which nodes perform actions (actuation) in response to sensor measurements and shared information, have great potential in medical and agricultural applications. In this paper, we focus on the problem of using distributed sensed data to design actuation strategies in order to elicit a desired response from the environment, whilst attempting to minimize the communication in the network. Our methodology is based on batch Q-learning; we describe a distributed approach for learning dyadic regression trees to estimate the Q-functions from collected data. Analysis and simulation indicate that substantial communication savings that can be achieved through distributed learning without significant performance deterioration. The simulations also reveal that the performance of our technique depends strongly on the amount of training data available

Published in:

2006 Third Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services

Date of Conference:

July 2006