scholarly journals Handling Trust in a Cloud based Multi Agent System

2021 ◽  
Author(s):  
Imen Bouabdallah ◽  
Hakima Mellah
Keyword(s):  
Cloud Services ◽  
Distributed Network ◽  
Multi Agent System ◽  
It Infrastructure ◽  
Multi Agent Systems ◽  
Swarm Optimization ◽  
Agent Systems ◽  
Security Breaches ◽  
Ongoing Work ◽  
Multi Agent

Cloud computing is an opened and distributed network that guarantees access to a large amount of data and IT infrastructure at several levels (software, hardware...). With the increase demand, handling clients’ needs is getting increasingly challenging. Responding to all requesting clients could lead to security breaches, and since it is the provider’s responsibility to secure not only the offered cloud services but also the data, it is important to ensure clients reliability. Although filtering clients in the cloud is not so common, it is required to assure cloud safety. In this paper, by implementing multi agent systems in the cloud to handle interactions for the providers, trust is introduced at agent level to filtrate the clients asking for services by using Particle Swarm Optimization and acquaintance knowledge to determine malicious and untrustworthy clients. The selection depends on previous knowledge and overall rating of trusted peers. The conducted experiments show that the model outputs relevant results, and even with a small number of peers, the framework is able to converge to the best solution. The model presented in this paper is a part of ongoing work to adapt interactions in the cloud.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 118-136 ◽  
Author(s):  
Robert E. Smith ◽  
Claudio Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

scholarly journals Quantum Diffie–Hellman Extended to Dynamic Quantum Group Key Agreement for e-Healthcare Multi-Agent Systems in Smart Cities

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3940
Author(s):  
Vankamamidi S. Naresh ◽  
Moustafa M. Nasralla ◽  
Sivaranjani Reddi ◽  
Iván García-Magariño
Keyword(s):  
System Architecture ◽  
Key Agreement ◽  
Unitary Operation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Group Key ◽  
Group Key Agreement ◽  
Agent Systems ◽  
Diffie Hellman ◽  
Multi Agent

Multi-Agent Systems can support e-Healthcare applications for improving quality of life of citizens. In this direction, we propose a healthcare system architecture named smart healthcare city. First, we divide a given city into various zones and then we propose a zonal level three-layered system architecture. Further, for effectiveness we introduce a Multi-Agent System (MAS) in this three-layered architecture. Protecting sensitive health information of citizens is a major security concern. Group key agreement (GKA) is the corner stone for securely sharing the healthcare data among the healthcare stakeholders of the city. For establishing GKA, many efficient cryptosystems are available in the classical field. However, they are yet dependent on the supposition that some computational problems are infeasible. In light of quantum mechanics, a new field emerges to share a secret key among two or more members. The unbreakable and highly secure features of key agreement based on fundamental laws of physics allow us to propose a Quantum GKA (QGKA) technique based on renowned Quantum Diffie–Hellman (QDH). In this, a node acts as a Group Controller (GC) and forms 2-party groups with remaining nodes, establishing a QDH-style shared key per each two-party. It then joins these keys into a single group key by means of a XOR-operation, acting as a usual group node. Furthermore, we extend the QGKA to Dynamic QGKA (DQGKA) by adding join and leave protocol. Our protocol performance was compared with existing QGKA protocols in terms of Qubit efficiency (QE), unitary operation (UO), unitary operation efficiency (UOE), key consistency check (KCC), security against participants attack (SAP) and satisfactory results were obtained. The security analysis of the proposed technique is based on unconditional security of QDH. Moreover, it is secured against internal and external attack. In this way, e-healthcare Multi-Agent System can be robust against future quantum-based attacks.

Adaptive Cooperation for Multi Agent Systems Based on Human Social Behavior

2012 ◽  
Vol 16 (1) ◽  
pp. 139-146 ◽  
Author(s):  
Hiroshi Igarashi ◽  
◽  
Yoshinobu Adachi ◽  
Kazunari Takahashi ◽  
◽  
...  
Keyword(s):  
Task Performance ◽  
Biological Knowledge ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Environmental Variations ◽  
Multi Agent ◽  
Multiple Robot ◽  
Robot Cooperation ◽  
Human Social Behaviour

This paper addresses a new cooperation technique for multi-agent systems. This technique is based on human social behaviour. According to biological knowledge, the population contributes to the preservation of the species and adaptability to environmental variations. Multiple robot cooperation, therefore, has a potential to be flexible and adaptable to various tasks. Furthermore, sociality based on the performance evaluation of other humans is expected to enhance the whole task performance. Finally, adaptability and the total performance of proposed technique are verified by pursuit survey on the multi-agent system.

Bounded consensus tracking control of second-order multi-agent systems with active leader and jointly connected topology

2016 ◽  
Vol 40 (2) ◽  
pp. 504-513 ◽  
Author(s):  
Lei Chen ◽  
Kaiyu Qin ◽  
Jiangping Hu
Keyword(s):  
Tracking Control ◽  
Sufficient Conditions ◽  
Interaction Network ◽  
Second Order ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Agent Systems ◽  
Strongly Connected ◽  
Multi Agent

In this paper, we investigate a tracking control problem for second-order multi-agent systems. Here, the leader is self-active and cannot be completely measured by all the followers. The interaction network associated with the leader–follower multi-agent system is described by a jointly connected topology, where the topology switches over time and is not strongly connected during each time subinterval. We consider a consensus control of the multi-agent system with or without time delay and propose two categories of neighbour-based control rules for every agent to track the leader, then provide sufficient conditions to ensure that all agents follow the leader, and meanwhile, the tracking errors can be estimated. Finally, some simulation results are presented to demonstrate our theoretical results.

scholarly journals On Partially Controlled Multi-Agent Systems

1996 ◽  
Vol 4 ◽  
pp. 477-507 ◽  
Author(s):  
R. I. Brafman ◽  
M. Tennenholtz
Keyword(s):  
Expected Utility ◽  
The Other ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Direct Control ◽  
Agent System ◽  
Agent Systems ◽  
Multi Agent ◽  
Game Theoretic

Motivated by the control theoretic distinction between controllable and uncontrollable events, we distinguish between two types of agents within a multi-agent system: controllable agents, which are directly controlled by the system's designer, and uncontrollable agents, which are not under the designer's direct control. We refer to such systems as partially controlled multi-agent systems, and we investigate how one might influence the behavior of the uncontrolled agents through appropriate design of the controlled agents. In particular, we wish to understand which problems are naturally described in these terms, what methods can be applied to influence the uncontrollable agents, the effectiveness of such methods, and whether similar methods work across different domains. Using a game-theoretic framework, this paper studies the design of partially controlled multi-agent systems in two contexts: in one context, the uncontrollable agents are expected utility maximizers, while in the other they are reinforcement learners. We suggest different techniques for controlling agents' behavior in each domain, assess their success, and examine their relationship.

scholarly journals Rational verification: game-theoretic verification of multi-agent systems

2021 ◽  
Author(s):  
Alessandro Abate ◽  
Julian Gutierrez ◽  
Lewis Hammond ◽  
Paul Harrenstein ◽  
Marta Kwiatkowska ◽  
...  
Keyword(s):  
Computer Science ◽  
Temporal Logic ◽  
State Of The Art ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
The Past ◽  
Multi Agent ◽  
Game Theoretic ◽  
Temporal Logic Formula

AbstractWe provide a survey of the state of the art of rational verification: the problem of checking whether a given temporal logic formula ϕ is satisfied in some or all game-theoretic equilibria of a multi-agent system – that is, whether the system will exhibit the behavior ϕ represents under the assumption that agents within the system act rationally in pursuit of their preferences. After motivating and introducing the overall framework of rational verification, we discuss key results obtained in the past few years as well as relevant related work in logic, AI, and computer science.

scholarly journals Nonlinear Attitude and Formation Estimation Spacecraft And Multi-Agent Systems

2021 ◽  
Author(s):  
Michael Rososhansky
Keyword(s):  
Particle Filter ◽  
Nonlinear Filtering ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Consensus Tracking ◽  
Multi Agent ◽  
Filtering Technique ◽  
Estimation And Control ◽  
And Control

This dissertation examines the state and parameter estimation problem of monolithic spacecraft and multi-agent systems in conjunction with the control algorithms. Nonlinear filtering techniques are investigated and applied to the problems of attitude estimation and control of monolithic spacecraft, distributed flltering for attitude estimation and control of satellite formation flying (SFF), and estimation and control of a multi-agent system in consensus tracking with uncertain dynamic model. The main objective is to investigate the performance of nonlinear filtering techniques under fault-free and fault-prone scenarios. In essence, the core of this research has been placed on identifying techniques to improve the efficiency and reduce the variance of estimations in nonlinear filtering. The research is primarily dedicated to the investigation of adaptive unscented Kalman Filter (AUKF) and particle Filter (PF). A nonlinear filtering technique has been proposed for sequential joint estimation of a multi-agent system in consensus tracking with uncertain dynamic model. The new filter is called marginalized unscented particle Filter (MUPF). The proposed filter uses the Rao-Blackwellised principle to couple the particle filtering technique with unscented transform algorithm

scholarly journals Multi-agent system for computer science and engineering education

2017 ◽  
Vol 58 ◽  
Author(s):  
Jaroslav Meleško ◽  
Eugenijus Kurilovas ◽  
Irina Krikun
Keyword(s):  
Learning Styles ◽  
Intelligent Agents ◽  
Educational Data Mining ◽  
Software Agent ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Agent Systems ◽  
Multi Agent ◽  
Identification Software

The paper aims to analyse application trends of intelligent multi-agent systems to personalise learning. First of all, systematic literature review was performed. Based on the systematic review analysis, the main trends on applying multi-agent systems to personalise learning were identified. Second, main requirements and components for an educational multi-agent system were formulated. Third, based on these components a model of intelligent personalized system is proposed. The system employs five intelligent agents: (1) learning styles identification software agent, (2) learner profile creation software agent, (3) pedagogical suitability software agent, (4) optimal learning units/scenarios creation software agent, and (5) learning analytics/educational data mining software agent.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 2338-2350
Author(s):  
Robert E. Smith ◽  
Claudia Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

The architecture and functionality of the multi-agent system Navigation

2017 ◽  
pp. 083-096
Author(s):  
A.L. Yalovets ◽  
Keyword(s):  
System Architecture ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Design Development ◽  
Agent System ◽  
Language Implementation ◽  
Agent Systems ◽  
Multi Agent

The features of the design, development and functioning of the multi-agent system Navigation are investigated. System architecture and substantiate the choice of language implementation of the system are provided. The functionality of the subsystems of multi-agent systems Navigation is analyzed in detail. The results of multi-agent modelling of pursuit/escape processes by means of the multi-agent system in different modes of its functioning are compared on meaningful example.

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