Abstract
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, 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.
Highlights
According to reference [1], the Internet of Things (IoT) can be defined as “made out of networked sensors and smart objects whose purpose is to measure/control/operate on an environment in such a way to make it intelligent, usable, programmable, and capable of providing useful services to humans.”This definition calls for ubiquitous intelligence where everyday physical objects should be able to join an IoT network where software components are required to behave intelligently—that is, for instance, understanding their own goals as well as the context where they operate
A goal is demonstrated against a logic theory that is considered true within a interval of time and within a region of space. Notice that this helps in dealing with the issue of guaranteeing global consistency in large-scale, ever-changing scenarios, such as the IoT; with Logic Programming as a Service (LPaaS), local consistency within individual knowledge bases distributed over the network suffices to support local reasoning
This is the way in which LPaaS supports temporal situatedness, that is, the ability to be aware of time passing by and the fact that, in dynamic scenarios like the IoT, the knowledge base represents truth at a given point in time
Summary
According to reference [1], the Internet of Things (IoT) can be defined as “made out of networked sensors and smart objects whose purpose is to measure/control/operate on an environment in such a way to make it intelligent, usable, programmable, and capable of providing useful services to humans.”. We discuss Logic Programming as a Service (LPaaS) [19] both as an enabling technology and in terms of the way it is developed, and advocate its role as a provider of symbolic reasoning techniques in IoT scenarios, complementing non-symbolic ones To this end, we move from the LPaaS re-interpretation of distributed logic programming [20] in the IoT era, which re-casts logic programming as a microservice that is deployable in compliance with the current agile software development and continuous delivery best practices.
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