LPaaS as Micro-intelligence: Enhancing IoT with Symbolic Reasoning

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Big Data and Cognitive Computing 2(3), article 23 (26 pages)

In 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, still symbolic approaches to machine intelligence 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.

keywordsLogic Programming as a Service, IoT, symbolic reasoning
journal or series
book Big Data and Cognitive Computing (BDCC)