Implementing virtual pheromones in BDI robots using MQTT and Jason

Bottone, Michele ORCID logoORCID: https://orcid.org/0009-0008-2515-4184, Palumbo, Filippo, Primiero, Giuseppe, Raimondi, Franco ORCID logoORCID: https://orcid.org/0000-0002-9508-7713 and Stocker, Richard (2016) Implementing virtual pheromones in BDI robots using MQTT and Jason. 2016 5th IEEE International Conference on Cloud Networking (Cloudnet). In: 2016 5th IEEE International Conference on Cloud Networking (Cloudnet), 03-05 Oct 2016, Pisa, Italy. ISBN 9781509050932. [Conference or Workshop Item] (doi:10.1109/CloudNet.2016.22)

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Abstract

Robotic coordination is a crucial issue in the development of many applications in swarm robotics, ranging from mapping unknown and potentially dangerous areas to the synthesis of plans to achieve complex tasks such as moving goods between locations under resource constraints. In this context, stigmergy is a widely employed approach to robotic coordination based on the idea of interacting with the environment by means of markers called pheromones. Pheromones do not need to be "physical marks", and a number of works have investigated the use of digital, virtual pheromones. In this paper, we show how the concept of virtual pheromones can be implemented in Jason, a Java-based interpreter for an extended version of AgentSpeak, providing a high-level modelling and execution environment for multi-agent systems. We also exploit MQTT, a messaging infrastructure for the Internet-of-Things. This allows the implementation of stigmergic algorithms in a high-level declarative language, building on top of low-level infrastructures typically used only for controlling sensors and actuators.

Item Type: Conference or Workshop Item (Paper)
Additional Information: M. Bottone, F. Palumbo, G. Primiero, F. Raimondi and R. Stocker, "Implementing Virtual Pheromones in BDI Robots Using MQTT and Jason (Short Paper)," 2016 5th IEEE International Conference on Cloud Networking (Cloudnet), Pisa, 2016, pp. 196-199. doi: 10.1109/CloudNet.2016.22
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 21921
Notes on copyright: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Depositing User: Michele Bottone
Date Deposited: 07 Jun 2017 13:48
Last Modified: 22 May 2023 16:41
URI: https://eprints.mdx.ac.uk/id/eprint/21921

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