An intelligent framework to manage robotic autonomous agents

Vidoni, Renato; García‐Sánchez, Francisco; Gasparetto, Alessandro; Martı́nez-Béjar, Rodrigo

doi:10.1016/j.eswa.2010.12.080

Cited by 16 publications

(6 citation statements)

References 32 publications

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“…Since Robotic Systems are evolving from industrial robots that are only responsible for one task, (performing it automatically), to autonomous and mobile robots that can collaborate among themselves and use sensors to understand their context, it was necessary to develop new systems to take advantage of all these new capabilities [3]. Taking this into account, it is possible to manage all these new features and requirements with a MAS.…”

Section: Distributed Systemsmentioning

confidence: 98%

Architecture and Message Protocol Proposal for Robot’s Integration in Multi-Agent Surveillance System

Dias¹,

Rodrigues²,

Claro³

et al. 2014

Lecture Notes in Computer Science

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Abstract. Nowadays, surveillance systems are less dependent of humans' interactions, mostly in event's detection. However, there still are tasks to be performed by humans that could be delegated to autonomous robots. The integration of an autonomous service robot, as an agent, in a multi-agent surveillance system can reduce even more humans' dependency. This paper proposes a new architecture and a communication protocol that integrates ServRobot's autonomous robot into DVA's surveillance system. This integration allows the DVA's system to use the robot as a mobile unit for validation of triggered events, to perform surveillance missions and to gather sensors information.

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Section: Distributed Systemsmentioning

confidence: 98%

Architecture and Message Protocol Proposal for Robot’s Integration in Multi-Agent Surveillance System

Dias¹,

Rodrigues²,

Claro³

et al. 2014

Lecture Notes in Computer Science

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“…The ontologies have already been applied in various domains, such as chemicals (Brandt et al ., 2008), robotics (Vidoni et al ., 2011), and medicine (Bertaud-Gounot et al ., 2012; Harispe et al ., 2014), as well as innovation and creativity. It has been implemented in the design field (Brandt et al ., 2008; Lee et al ., 2009; Afacan and Demirkan, 2011) or R&D management (Hernández-González et al ., 2014).…”

Section: Representing the Knowledge Domainmentioning

confidence: 99%

Methodology to design ontologies from organizational models: application to creativity workshops

Gabriel¹,

Chavez²,

Monticolo³

2019

AIEDAM

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Innovation and creativity are a mandatory for companies who wish to stay competitive. In order to promote an inventive dynamic, it implies to set up tools, habits, and an adapted environment to foster creativity. Creativity is the wealth of companies that should be valorized. To promote creativity, companies implement creativity workshops that gather people with various roles and expertise exchange and create knowledge to solve collectively open-ended engineering problems. However, group dynamics or facilitation can make the wrong decision and make the creative problem-solving unfruitful. The aim of our research project is to create a digital system to manage and valorize knowledge during creativity workshops. To design this system, we need to formalize the knowledge domain of creative workshops. The ontologies are used for decades to structure and manage information and knowledge in different domains. However, methodologies to design these ontologies are either hardly reproducible or not oriented to extract knowledge from organization. This article describes a methodology based on an organizational modeling to build ontologies. We will illustrate our approach by designing an ontology that models knowledge of creativity workshops.

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“…price of goods, delivery terms, or payment conditions), cooperate, and even compete with each other to satisfy their individual and social goals, which they cannot achieve alone (due to the lack of resources, capabilities, or knowledge) (Weiss, 1999). Another crucial reason is that today’s applications of MASs ranging from agent-based Web services and their communities (Bentahar et al ., 2008), human learners (Sklar & Richards, 2010), software agent-based interaction models (Cabri et al , 2010), robotic agents (Nakano et al , 2011; Vidoni et al , 2011), multi-sensory and distributed surveillance (Gascueña & Fernández-Caballero, 2011), agent-based computational economic models (Richiardia, 2012), manufacturing systems (Lim & Zhang, 2012) to Web service composition (Lomuscio et al , 2012), have one thing in common: The agents employed in those systems should communicate with each other. It is clear that the success of those MASs requires commonly understood languages: lingua franca for agents to talk to each other in order to determine what proper information to exchange or what right action to take as well as powerful mechanisms (protocols) to regulate and coordinate communication among participants within conversations.…”

Section: Introductionmentioning

confidence: 99%

Computational logics and verification techniques of multi-agent commitments: survey

Menshawy¹,

Kholy²,

Yolum

et al. 2015

The Knowledge Engineering Review

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Agent communication languages (ACLs) are fundamental mechanisms that enable agents in multi-agent systems totalk, communicate with each other in order to satisfy their individual and social goals in a cooperative and competitive manner. Social approaches are advocated to overcome the shortcomings of ACL semantics delineated by using mental approaches in the figure of agents’ mental notions. Over the last two decades,socialcommitments have been the subject of considerable research in some of those social approaches as they provide a powerful representation for modeling and reasoning upon multi-agent interactions in the form of mutual contractual obligations. They particularly provide a declarative, flexible, verifiable, and social semantics for ACL messages while respecting agents’ autonomy, heterogeneity, and openness.In this manuscript, we go through prominent and predominate proposals in the literature to explore the state of the art on how temporal logics can be devoted to define a formal semantics for ACL messages in terms of social commitments and associated actions. We explain each proposal and point out if and how it meetssevencrucial criteria, four of them introduced by Munindar P. Singh to have a well-defined semantics for ACL messages. Far from deciding the best proposal, our aim is to present the advantages (strengths) and limitations of those proposals to designers and developers using a concrete running example and to compare between them, so that they can make the best choice with regard to their needs. We explore and evaluate current specification languages and different verification techniques that have been discussed within those proposals to, respectively, specify and verify commitment-based protocols. We also investigate logical languages of actions advocated to specify, model, and execute commitment-based protocols in other contributed proposals. Finally, we suggest some solutions that can contribute to address the identified limitations.

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An intelligent framework to manage robotic autonomous agents

Cited by 16 publications

References 32 publications

Architecture and Message Protocol Proposal for Robot’s Integration in Multi-Agent Surveillance System

Architecture and Message Protocol Proposal for Robot’s Integration in Multi-Agent Surveillance System

Methodology to design ontologies from organizational models: application to creativity workshops

Computational logics and verification techniques of multi-agent commitments: survey

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