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1.
Anomaly detection is a basic functionality of intrusion detection systems. The aim of such systems in distributed computer communication systems is to recognize and notify about various events that influence a system's security. In a gain to assure efficiency, flexibility, and a quality of detection of systems security violation in a distributed environment, required detection systems should be responsive, adaptive, proactive, and less centralized than those currently deployed. Such required properties are offered by agents and multiagent systems, i.e., agent-based technology has the continuously increasing potential to offer a solution to the growing problem of designing intelligent, efficient, and flexible management systems. An agent-based approach offers the potential to develop advanced and effective distributed, network-based strategies replacing traditional node-based approaches by more perspective network-based approaches.

This article is devoted to present various architectures of anomaly detection systems, which may be implemented as multiagent systems supporting the classification of observed activities as normal or abnormal. Some simple example presents hierarchical architecture of a distributed anomaly detection system, which may be implemented in the form of a multiagent decision supporting system.  相似文献   

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This paper presents an architectural framework for cooperating knowledge based systems (CKBSs) with parallels drawn from the multiagent systems of DAI. A CKBS is distinguished from a multiagent system by its need to provide a workable approach for real-world distributed applications. The framework proposed considers only interagent activities in what is called transaction-oriented processing. The framework, based largely on well-tested computer science concepts, provides for a multilayered edifice with information transparency, and a multilevel schema to suit different user expertise. It permits dynamic definition of cooperation strategies for different tasks as required, in a high-level language providing relative ease of use. A particular novelty is the interpretation of actions as side-effects of update operations on action tuples transmitted among agents via what are called shadows. This provides the generality needed. Effectiveness, flexibility, and ease of use are some of the key considerations  相似文献   

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Rationality alone is insufficient to specify agent design. Using economic theory, we can program agents to behave in ways that maximize their utility while responding to environmental changes. However, economic models for agents, although general in principle, are typically limited in practice because the value functions that are tractable essentially reduce an agent to acting selfishly. Building a stable social system from a collection of agents motivated by self-serving interests is difficult. Finally, understanding rationality and knowledge requires interdisciplinary results from artificial intelligence, distributed computing, economics and game theory, linguistics, philosophy, and psychology. A complete theory involves semantic models for knowledge, belief, action, uncertainty; bounded rationality and resource-bounded reasoning; commonsense epistemic reasoning; reasoning about mental states; belief revision; and interactions in multiagent systems.  相似文献   

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In a multiagent system where norms are used to regulate the actions agents ought to execute, some agents may decide not to abide by the norms if this can benefit them. Norm enforcement mechanisms are designed to counteract these benefits and thus the motives for not abiding by the norms. In this work we propose a distributed mechanism through which agents in the multiagent system that do not abide by the norms can be ostracised by their peers. An ostracised agent cannot interact anymore and looses all benefits from future interactions. We describe a model for multiagent systems structured as networks of agents, and a behavioural model for the agents in such systems. Furthermore, we provide analytical results which show that there exists an upper bound to the number of potential norm violations when all the agents exhibit certain behaviours. We also provide experimental results showing that both stricter enforcement behaviours and larger percentage of agents exhibiting these behaviours reduce the number of norm violations, and that the network topology influences the number of norm violations. These experiments have been executed under varying scenarios with different values for the number of agents, percentage of enforcers, percentage of violators, network topology, and agent behaviours. Finally, we give examples of applications where the enforcement techniques we provide could be used.  相似文献   

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Organizations influence many aspects of our lives. They exist for one reason: they can accomplish things that individuals cannot. While recent work in high-autonomy systems has shown that autonomy is a critical issue in artificial intelligence (AI) systems, these systems must also be able to cooperate with and rely on one another to deal with complex problems. The autonomy of such systems must be flexible, in order that agents may solve problems on their own as well as in groups. We have developed a model of distributed problem solving in which coordination of problem-solving agents is viewed as a multiagent constraint-satisfaction planning problem. This paper describes the experimental testbed that we are currently developing to facilitate the investigation of various constraint-based strategies for addressing the coordination issues inherent in cooperative distributed problem-solving domains.  相似文献   

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On load balancing for distributed multiagent computing   总被引:1,自引:0,他引:1  
Multiagent computing on a cluster of workstations is widely envisioned to be a powerful paradigm for building useful distributed applications. The agents of the system span across all the machines of a cluster. Just like the case of traditional distributed systems, load balancing becomes an area of concern. With different characteristics between ordinary processes and agents, it is both interesting and useful to investigate whether conventional load-balancing strategies are also applicable and sufficient to cope with the newly emerging needs, such as coping with temporally continuous agents, devising a performance metric for multiagent systems, and taking into account the vast amount of communication and interaction among agent. This paper discusses the above issues with reference to agent properties and load balancing techniques and outlines the space of load-balancing design choices in the arena of multiagent computing. In view of the special agent characteristics, a novel communication-based load-balancing algorithm is proposed, implemented, and evaluated. The proposed algorithm works by associating a credit value with each agent. The credit of an agent depends on its affinity to a machine, its current workload, its communication behavior, and mobility, etc. When a load imbalance occurs, the credits of all agents are examined and an agent with a lower credit value is migrated to relatively lightly loaded machine in the system. Quasi-simulated experiments of this algorithm show load-balancing improvement compared with conventional workload-oriented load-balancing schemes.  相似文献   

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The study of distributed computational systems issues, such as heterogeneity, concurrency, control, and coordination, has yielded a number of models and architectures, which aspire to provide satisfying solutions to each of the above problems. One of the most intriguing and complex classes of distributed systems are computational ecosystems, which add an "ecological" perspective to these issues and introduce the characteristic of self-organization. Extending previous research work on self-organizing communities, we have developed Biotope, which is an agent simulation framework, where each one of its members is dynamic and self-maintaining. The system provides a highly configurable interface for modeling various environments as well as the "living" or computational entities that reside in them, while it introduces a series of tools for monitoring system evolution. Classifier systems and genetic algorithms have been employed for agent learning, while the dispersal distance theory has been adopted for agent replication. The framework has been used for the development of a characteristic demonstrator, where Biotope agents are engaged in well-known vital activities-nutrition, communication, growth, death-directed toward their own self-replication, just like in natural environments. This paper presents an analytical overview of the work conducted and concludes with a methodology for simulating distributed multiagent computational systems.  相似文献   

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In distributed and open environments, MASs (multiagent systems) generally have no mechanisms for prior coordination and self‐organization has been believed to be the necessary selection to achieve the coordination of agents. This paper first presents a values‐driven model for self‐organization in which the expected emergent properties of a system are specified as the social values while the social values are realized via implicitly inducing members to regulate their individual values and adjust their behaviors to fit the expectations of the system. Based on the values‐driven self‐organization, this paper proposes an automated coordination mechanism for decentralized MASs. In this mechanism, by indirectly changing the difficulties in acquiring resources (which may be delegated to some special agents since MASs generally do not have substantial bodies), MASs can lead agents to regulate their values to be consistent with the social values of MASs so that the coordination of MASs can spontaneously emerge from the local behaviors of agents. Finally, this paper implements a simulation traffic system using the coordination mechanism based on values‐driven self‐organization to validate the emergence of coordination among multiple agents.  相似文献   

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