From raw data to agent perceptions for simulation, verification, and monitoring

Bottone, Michele, Primiero, Giuseppe, Raimondi, Franco ORCID logoORCID: and Rungta, Neha (2016) From raw data to agent perceptions for simulation, verification, and monitoring. Intelligent Environments 2016 - Workshop Proceedings of the 12th International Conference on Intelligent Environments. In: 12th International Conference on Intelligent Environment 2016:- 5th International Workshop on Reliability of Intelligent Environments (WoRIE’16), 14-16 Sept 2016, London, United Kingdom. ISBN 9781614996897. [Conference or Workshop Item] (doi:10.3233/978-1-61499-690-3-66)

PDF - Published version (with publisher's formatting)
Available under License Creative Commons Attribution-NonCommercial 4.0.

Download (284kB) | Preview


In this paper we present a practical solution to the problem of connecting “real world” data exchanged between sensors and actuators with the higher level of abstraction used in frameworks for multiagent systems. In particular, we show how to connect an industry-standard publish-subscribe communication protocol for embedded systems called MQTT with two Belief-Desire-Intention agent modelling and programming languages: Jason/AgentSpeak and Brahms. In the paper we describe the details of our Java implementation and we release all the code open source.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Series: Ambient Intelligence and Smart Environments, Volume 21: Intelligent Environments 2016
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 21920
Notes on copyright: © 2016 The authors and IOS Press.
This article is published online with Open Access by IOS Press and distributed under the terms
of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0)
Useful Links:
Depositing User: Michele Bottone
Date Deposited: 07 Jun 2017 13:47
Last Modified: 29 Nov 2022 21:35

Actions (login required)

View Item View Item


Activity Overview
6 month trend
6 month trend

Additional statistics are available via IRStats2.