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Project Abstracts Return to Sensor and Actuator Networks Projects

Optimal Actuation Strategies for Sensor/Actuator Networks
 

Student: Frederic Thouin, Ph.D. Student and Richard Thommes, Ph.D.
Supervisor: Prof. Mark Coates

Abstract: 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 (i)substantial communication savings can be achieved through distributed learning without significant performance deterioration and (ii)the performance of our technique depends strongly on the amount of training data available.

[Paper (pdf format)]