Multi-Agent Systems: A Survey

Dorri, Ali; Kanhere, Salil S.; Jurdak, Raja

doi:10.1109/access.2018.2831228

Cited by 602 publications

(314 citation statements)

References 139 publications

Supporting

Mentioning

309

Contrasting

Unclassified

Order By: Relevance

“…In order to satisfy the requirements, this subsection proposes a programming model by adopting the concept of an MAS. Traditionally, an agent in an MAS is defined as an autonomous entity with intelligence [49]. An entity senses various parameters from the external environment that are then used to make a decision.…”

Section: An Agent-based Interoperable Programming Modelmentioning

confidence: 99%

Fog BEMS: An Agent-Based Hierarchical Fog Layer Architecture for Improving Scalability in a Building Energy Management System

Lee

2020

Sustainability

View full text Add to dashboard Cite

It has been found that a cloud building energy management system (BEMS) alone cannot support increasing numbers of end devices (e.g., energy equipment and IoT devices) and emerging energy services efficiently. To resolve these limitations, this paper proposes Fog BEMS, which applies an emerging fog computing concept to a BEMS. Fog computing places small computing resources (fog nodes) just next to end devices, and these nodes process data in real time and manage local contexts. In this way, the BEMS becomes distributed and scalable. However, existing fog computing models have barely considered scenarios where many end devices and fog nodes are deployed and interconnected. That is, they do not scale up and cannot be applied to scalable applications like BEMS. To solve the problem, this paper (i) designs a fog network where a list of functionally heterogeneous nodes is deployed in a hierarchy for collaboration and (ii) designs an agent-based, modular programming model that eases the development and management of computing services at a fog node. We develop a prototype of a fog node and build a real-world testbed on a campus to demonstrate the feasibility of the proposed system. We also conduct experiments, and results show that Fog BEMS is scalable enough for a node to connect up to 900 devices and that network traffic is reduced by 27.22–97.63%, with varying numbers of end devices.

show abstract

Section: An Agent-based Interoperable Programming Modelmentioning

confidence: 99%

Fog BEMS: An Agent-Based Hierarchical Fog Layer Architecture for Improving Scalability in a Building Energy Management System

Lee

2020

Sustainability

View full text Add to dashboard Cite

show abstract

“…However, while being a long investigated topic, most developed mechanisms still suffer from exhaustive resource consumption and are centralized by nature, i.e. require an overall monitoring entity and are thus unable to scale up to large installations [3], [4]. Furthermore, isolation of (identified) faulty nodes is an open issue [4].…”

Section: Introductionmentioning

confidence: 99%

A Subjective-Logic-based Reliability Estimation Mechanism for Cooperative Information with Application to IV's Safety

Müller

Gabb

Buchholz

2019

2019 IEEE Intelligent Vehicles Symposium (IV)

View full text Add to dashboard Cite

Use of cooperative information, distributed by road-side units, offers large potential for intelligent vehicles (IVs). As vehicle automation progresses and cooperative perception is used to fill the blind spots of onboard sensors, the question of reliability of the data becomes increasingly important in safety considerations (SOTIF, Safety of the Intended Functionality).This paper addresses the problem to estimate the reliability of cooperative information for in-vehicle use. We propose a novel method to infer the reliability of received data based on the theory of Subjective Logic (SL). Using SL, we fuse multiple information sources, which individually only provide mild cues of the reliability, into a holistic estimate, which is statistically sound through an end-to-end modeling within the theory of SL.Using the proposed scheme for probabilistic SL-based fusion, IVs are able to separate faulty from correct data samples with a large margin of safety. Real world experiments show the applicability and effectiveness of our approach.

show abstract

“…However, intentionally malicious agents have not been included so far. Furthermore, according to the MAS survey [6] published in October 2018, FDI methods still suffer from the following severe limitations: 1) most mechanisms assume homogeneous agents, while in an open MAS such as ITS, this assumption is not justified, 2) exhaustive resource consumption, 3) isolating faulty nodes is an open issue and 4) most of the proposed solutions are centralized by nature. The mechanism described within this work offers a proposition how these shortcomings can be addressed.…”

Section: Introductionmentioning

confidence: 99%

A Trust Management and Misbehaviour Detection Mechanism for Multi-Agent Systems and its Application to Intelligent Transportation Systems

Müller

Meuser

Steinmetz

et al. 2019

2019 IEEE 15th International Conference on Control and Automation (ICCA)

View full text Add to dashboard Cite

Cooperative information shared among a multiagent system (MAS) can be useful to agents to efficiently fulfill their missions. Relying on wrong information, however, can have severe consequences. While classical approaches only consider measurement uncertainty, reliability information on the incoming data can be useful for decision making. In this work, a subjective logic based mechanism is proposed that amends reliability information to the data shared among the MAS. If multiple agents report the same event, their information is fused. In order to maintain high reliability, the mechanism detects and isolates misbehaving agents. Therefore, an attacker model is specified that includes faulty as well as malicious agents. The mechanism is applied to Intelligent Transportation Systems (ITS) and it is shown in simulation that the approach scales well with the size of the MAS and that it is able to efficiently detected and isolated misbehaving agents.

show abstract

Multi-Agent Systems: A Survey

Cited by 602 publications

References 139 publications

Fog BEMS: An Agent-Based Hierarchical Fog Layer Architecture for Improving Scalability in a Building Energy Management System

Fog BEMS: An Agent-Based Hierarchical Fog Layer Architecture for Improving Scalability in a Building Energy Management System

A Subjective-Logic-based Reliability Estimation Mechanism for Cooperative Information with Application to IV's Safety

A Trust Management and Misbehaviour Detection Mechanism for Multi-Agent Systems and its Application to Intelligent Transportation Systems

Contact Info

Product

Resources

About