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Modified Backward Chaining Algorithm Using Artificial Intelligence Planning IoT Applications

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dc.contributor.author K., Pradheep Kumar
dc.date.accessioned 2023-01-17T10:17:09Z
dc.date.available 2023-01-17T10:17:09Z
dc.date.issued 2019
dc.identifier.uri https://www.igi-global.com/chapter/modified-backward-chaining-algorithm-using-artificial-intelligence-planning-iot-applications/232006
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8522
dc.description.abstract In this chapter, an automated planning algorithm has been proposed for IoT-based applications. A plan is a sequence of activities that leads to a goal or sub-goals. The sequence of sub-goals leads to a particular goal. The plans can be formulated using forward chaining where actions lead to goals or by backward chaining where goals lead to actions. Another method of planning is called partial order planning where all actions and sub-goals are not illustrated in the plan and left incomplete. When many IoT devices are interconnected, based on the tasks and activities involved resource allocation has to be optimized. An optimal plan is one where the total plan length is minimum, and all actions consume similar quantum of resources to achieve a goal. The scheduling cost incurred by way of resource allocation would be minimum. Compared to the existing algorithms L2-Plan (Learn to Plan) and API, the algorithm developed in this work improves optimality of resources by 14% and 36%, respectively en_US
dc.language.iso en en_US
dc.publisher IGI Global en_US
dc.subject Computer Science en_US
dc.subject Artificial Intelligence en_US
dc.subject IoT Applications en_US
dc.subject Algorithm en_US
dc.title Modified Backward Chaining Algorithm Using Artificial Intelligence Planning IoT Applications en_US
dc.type Article en_US


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