LPaaS as Micro-Intelligence: Enhancing IoT with Symbolic Reasoning
AbstractIn the era of Big Data and IoT, successful systems have to be designed to discover, store, process, learn, analyse, and predict from a massive amount of data—in short, they have to behave intelligently. Despite the success of non-symbolic techniques such as deep learning, symbolic approaches to machine intelligence still have a role to play in order to achieve key properties such as observability, explainability, and accountability. In this paper we focus on logic programming (LP), and advocate its role as a provider of symbolic reasoning capabilities in IoT scenarios, suitably complementing non-symbolic ones. In particular, we show how its re-interpretation in terms of LPaaS (Logic Programming as a Service) can work as an enabling technology for distributed situated intelligence. A possible example of hybrid reasoning—where symbolic and non-symbolic techniques fruitfully combine to produce intelligent behaviour—is presented, demonstrating how LPaaS could work in a smart energy grid scenario. View Full-Text
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Calegari, R.; Ciatto, G.; Mariani, S.; Denti, E.; Omicini, A. LPaaS as Micro-Intelligence: Enhancing IoT with Symbolic Reasoning. Big Data Cogn. Comput. 2018, 2, 23.
Calegari R, Ciatto G, Mariani S, Denti E, Omicini A. LPaaS as Micro-Intelligence: Enhancing IoT with Symbolic Reasoning. Big Data and Cognitive Computing. 2018; 2(3):23.Chicago/Turabian Style
Calegari, Roberta; Ciatto, Giovanni; Mariani, Stefano; Denti, Enrico; Omicini, Andrea. 2018. "LPaaS as Micro-Intelligence: Enhancing IoT with Symbolic Reasoning." Big Data Cogn. Comput. 2, no. 3: 23.
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