LPaaS as Micro-intelligence: Enhancing IoT with Symbolic Reasoning

Last modified by Andrea Omicini on 01/05/2021 16:48

Roberta Calegari, Giovanni Ciatto, Stefano Mariani, Enrico Denti, Andrea Omicini

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.

(keywords) Logic Programming as a Service, IoT, symbolic reasoning
Big Data and Cognitive Computing 2(3), 26 pages, article no. 23, 2018, MDPI
Articleno = 23,
Author = {Calegari, Roberta and Ciatto, Giovanni and Mariani, Stefano and Denti, Enrico and Omicini, Andrea},
Doi = {10.3390/bdcc2030023},
IrisId = {11585/640012},
Issn-Online = {2504-2289},
Journal = {Big Data and Cognitive Computing},
Keywords = {Logic Programming as a Service, IoT, symbolic reasoning},
Number = 3,
Numpages = 26,
Publisher = {MDPI},
Title = {{LPaaS} as Micro-intelligence: Enhancing {IoT} with Symbolic Reasoning},
Url = {http://www.mdpi.com/2504-2289/2/3/23},
Url-Pdf = {http://www.mdpi.com/2504-2289/2/3/23/pdf},
Volume = 2,
Year = 2018}


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