Jason-RS, A Collaboration Between Agents and an IoT Platform - Machine Learning for Networking
Conference Papers Year : 2020

Jason-RS, A Collaboration Between Agents and an IoT Platform

Hantanirina Felixie Rafalimanana
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  • PersonId : 1102752
Jean Luc Razafindramintsa
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Sylvain Cherrier
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Thomas Mahatody
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  • PersonId : 1102755
Laurent George
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Victor Manantsoa
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Abstract

In this article we start from the observation that REST services are the most used as tools of interoperability and orchestration in the Internet of Things (IoT). But REST does not make it possible to inject artificial intelligence into connected objects, i.e. it cannot allow autonomy and decision-making by the objects themselves. To define an intelligence to a connected object, one can use a Believe Desire Intention agent (BDI an intelligent agent that adopts human behavior) such as Jason Agentspeak. But Jason AgentSpeak does not guarantee orchestration or choreography between connected objects. There are platforms for service orchestration and choreography in IoT, still the interconnection with artificial intelligence needs to be built. In this article, we propose a new approach called Jason-RS. It is a result of pairing Jason BDI agent with the web service technologies to exploit the agent capacity as a service, Jason-RS turn in Java SE and it does not need any middleware. The architecture that we propose allows to create the link between Artificial Intelligence and Services choreography to reduce human intervention in the service choreography. In order to validate the proposed approach, we have interconnected the Iot BeC3 platform and the REST agent (Jason-RS). The decision-making faculty offered by Jason-RS is derived from the information sent by the objects according to the different methods of REST (GET, POST, PUT, and DELETE) that Jason-RS offers. As a result, the objects feed the inter-agent collaborations and decision-making inside the agent. Finally, we show that Jason-RS allows the Web of Objects to power complex systems such as an artificial intelligence responsible for processing data. This performance is promising.
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Dates and versions

hal-03266450 , version 1 (21-06-2021)

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Hantanirina Felixie Rafalimanana, Jean Luc Razafindramintsa, Sylvain Cherrier, Thomas Mahatody, Laurent George, et al.. Jason-RS, A Collaboration Between Agents and an IoT Platform. 2nd International Conference on Machine Learning for Networking (MLN), Dec 2019, Paris, France. pp.403-413, ⟨10.1007/978-3-030-45778-5_28⟩. ⟨hal-03266450⟩
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