scholarly journals JADE Multi-agent Middleware Applied to Contribute to Certificate Management of Students

2015 ◽  
Vol 16 (1) ◽  
pp. 176
Author(s):  
Fatiha Aityacine ◽  
Badr Hssina ◽  
Belaid Bouikhalene

In this article, we present a multi-agent approach that aims to design, modeling and implementation of an application "smart school". Indeed Several institutions adopt the computerized management of education to meet the needs of students using multi-agent systems. They have the ability to act simultaneously in a shared environment. The purpose of this approach is to automate some administrative services of education, based on the theory of distributed artificial intelligence (DAI) and multi-agent systems (MAS). This multi-agent application integrates entities called agents that cooperate and communicate them to perform specific tasks. Our system is based on the middleware JADE (Java Agent DEvelopment Framework) used for the implementation and agents management. This model based on multi-agent systems is tested on the personal data of an experiment conducted with the students of Sultan Moulay Slimane University in Beni Mellal.

2012 ◽  
Vol 614-615 ◽  
pp. 807-810
Author(s):  
Ye Liu ◽  
Shou Xiang Wang

In this paper, MAS is used to model the framework of smart grid. Multi-Agent Systems (MAS) is one of the popular method in Distributed Artificial Intelligence (DAI) in the past years, which is a good tools to simulate and model the complex systems. Several MAS develop platforms are exist. Considering that JADE (Java Agent Development Framework) is one of the helpful and convenient developing environments of MAS, JADE is adapted to develop smart grid control framework. In this paper, a suitable frame construction of the Multi-Agent Systems for the current power system is designed, which is applied to the smart grid with excellent adaptability and flexibility.


Author(s):  
Ronen Nir ◽  
Erez Karpas

Designing multi-agent systems, where several agents work in a shared environment, requires coordinating between the agents so they do not interfere with each other. One of the canonical approaches to coordinating agents is enacting a social law, which applies restrictions on agents’ available actions. A good social law prevents the agents from interfering with each other, while still allowing all of them to achieve their goals. Recent work took the first step towards reasoning about social laws using automated planning and showed how to verify if a given social law is robust, that is, allows all agents to achieve their goals regardless of what the other agents do. This work relied on a classical planning formalism, which assumed actions are instantaneous and some external scheduler chooses which agent acts next. However, this work is not directly applicable to multi-robot systems, because in the real world actions take time and the agents can act concurrently. In this paper, we show how the robustness of a social law in a continuous time setting can be verified through compilation to temporal planning. We demonstrate our work both theoretically and on real robots.


2021 ◽  
Author(s):  
Qin Yang

Distributed artificial intelligence (DAI) studies artificial intelligence entities working together to reason, plan, solve problems, organize behaviors and strategies, make collective decisions and learn. This Ph.D. research proposes a principled Multi-Agent Systems (MAS) cooperation framework -- Self-Adaptive Swarm System (SASS) -- to bridge the fourth level automation gap between perception, communication, planning, execution, decision-making, and learning.


Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 363 ◽  
Author(s):  
Davide Calvaresi ◽  
Jean-Paul Calbimonte ◽  
Alevtina Dubovitskaya ◽  
Valerio Mattioli ◽  
Jean-Gabriel Piguet ◽  
...  

The agent based approach is a well established methodology to model distributed intelligent systems. Multi-Agent Systems (MAS) are increasingly employed in applications dealing with safety and information critical tasks (e.g., in eHealth, financial, and energy domains). Therefore, transparency and the trustworthiness of the agents and their behaviors must be enforced. For example, employing reputation based mechanisms can promote the development of trust. Nevertheless, besides recent early stage studies, the existing methods and systems are still unable to guarantee the desired accountability and transparency adequately. In line with the recent trends, we advocate that combining blockchain technology (BCT) and MAS can achieve the distribution of the trust, removing the need for trusted third parties (TTP), potential single points of failure. This paper elaborates on the notions of trust, BCT, MAS, and their integration. Furthermore, to attain a trusted environment, this manuscript details the design and implementation of a system reconciling MAS (based on the Java Agent DEvelopment Framework (JADE)) and BTC (based on Hyperledger Fabric). In particular, the agents’ interactions, computation, tracking the reputation, and possible policies for disagreement-management are implemented via smart contracts and stored on an immutable distributed ledger. The results obtained by the presented system and similar solutions are also discussed. Finally, ethical implications (i.e., opportunities and challenges) are elaborated before concluding the paper.


2021 ◽  
Vol 70 ◽  
pp. 389-407
Author(s):  
Guangqiang Xie ◽  
Junyu Chen ◽  
Yang Li

As an important field of Distributed artificial intelligence (DAI), multi-agent systems (MASs) have attracted the attention of extensive research scholars. Consensus as the most important issue in MAS, much progress has been made in studying the consensus control of MAS, but there are some problems remained largely unaddressed which cause the MAS to lose some useful network structure information. First, multi-agent consensus protocol usually proceeds over the low-order structure by only considering the direct edges between agents, but ignores the higher-order structure of the whole topology network. Second, the existing work assumes all the edges in a topology network have the same weight without exploring the potential diversity of the connections. In this way, multi-agent systems fail to enforce consensus, resulting in fragmentation into multiple clusters. To address the above issues, this paper proposes a Motif-aware Weighted Multi-agent System (MWMS) method for consensus control. We focus more on triangle motif in the network, but it can be extended to other kinds of motifs as well. First, a novel weighted network is used which is the combination of the edge-based lower-order structure and the motif-based higher-order structure, i.e., hybrid-order structure. Subsequently, by simultaneously considering the quantity and the quality of the connections in the network, a novel consensus framework for MAS is designed to update agents. Then, two baseline consensus algorithms are used in MWMS. In our experiments, we use ten topologies of different shapes, densities and ranges to comprehensively analyze the performance of our proposed algorithms. The simulation results show that the hybrid higher-order network can effectively enhance the consensus of the multi-agent system in different network topologies.


2021 ◽  
Author(s):  
Sabine Topf ◽  
Maarten Speekenbrink

Stigmergy refers to the coordination of agents via artifacts of behaviours (behavioural traces) in the shared environment. Whilst primarily studied in biology and computer science/robotics, stigmergy underlies many human indirect interactions, both offline (e.g., trail building) and online (e.g., development of open-source software). In this review, we provide an introduction to stigmergy and emphasise how and where human stigmergy is distinct from animal or robot stigmergy, such as intentional communication via traces and causal inferences from the traces to the causing behaviour. Cognitive processes discussed on the agent level include attention, motivation, meaning and meta-cognition, as well as emergence/immergence, iterative learning and exploration/exploitation at the interface of individual agent and multi-agent systems. Characteristics of one-agent, two-agent and multi-agent systems are discussed and areas for future research highlighted.


2019 ◽  
Vol 4 (2) ◽  
pp. 193
Author(s):  
Very Sugiarto ◽  
Fatwa Ramdani ◽  
Fitra Bachtiar

One of the most fatal natural disasters in Batu City was a landslide. The percentage of casualties if directly affected by landslides is 47%. This number is quite large when compared to other natural disasters. Even though the potential of the tsunami is the biggest, when compared to the intensity of the occurrence, landslides are the most common and most often cause fatalities. One of the causes of many fatalities in natural disasters is the lack of preparedness management. For that reason the need to develop a technology that can support to reduce fatalities in landslides is needed. One of the technologies used to prevent the number of fatalities caused by natural disasters is to use multi-agent system. One of the advantages of an agent is use Belief-Desire-Intention (BDI) models for building the Muiti-Agent Systems (MAS). The specific objective of this study was to model a simulated natural disaster landslide using the Prometheus Methodology. Evaluation is done by generating a model using jackCode and implementing it using the Java Agent Development Framework. The results of this study indicate that a model made using the Prometheus Methodology can be used as a simulation of natural disaster preparedness for landslides.


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