Embedding intelligent decision making within complex dynamic environments

Decision-making is a complex and demanding process often constrained in a number of possibly conflicting dimensions including quality, responsiveness and cost. This paper considers in situ decision making whereby decisions are effected based upon inferences made from both locally sensed data and data aggregated from a sensor network. Such sensing devices that comprise a sensor network are often computationally challenged and present an additional constraint upon the reasoning process. This paper describes a hybrid reasoning approach to deliver in situ decision making which combines stream based computing with multi-agent system techniques. This approach is illustrated and exercised through an environmental demonstrator project entitled SmartBay which seeks to deliver in situ real time environmental monitoring. © 2008 Springer Science+Business Media B.V.