Efficient Approximate Inference in Distributed Bayesian Networks for MAS-based Sensor Interpretation (Short Paper)
نویسنده
چکیده
The multiply sectioned Bayesian network (MSBN) framework is the most studied approach for distributed Bayesian Network inference in an MAS setting. This paper describes a new framework that supports efficient approximate MASbased sensor interpretation, more autonomy and asynchrony among the agents, and more focused, situation-specific communication patterns. Its use can lead to significant improvements in agent utilization and time-to-solution.
منابع مشابه
Efficient approximate inference in distributed Bayesian networks for MAS-based sensor interpretation
The multiply sectioned Bayesian network (MSBN) framework is the most studied approach for distributed Bayesian Network inference in an MAS setting. This paper describes a new framework that supports efficient approximate MASbased sensor interpretation, more autonomy and asynchrony among the agents, and more focused, situation-specific communication patterns. Its use can lead to significant impr...
متن کاملA New Framework for Inference in Distributed Bayesian Networks for Multi-Agent Sensor Interpretation
Multi-agent systems (MAS) are groups of interacting intelligent software agents. An important application is sensor interpretation (SI) in sensor networks. SI domains are frequently modeled with Bayesian networks (BNs), and distributed versions of these problems can be modeled with distributed Bayesian networks (DBNs). The multiply sectioned Bayesian network (MSBN) framework is the most studied...
متن کاملAn Efficient Cluster Head Selection Algorithm for Wireless Sensor Networks Using Fuzzy Inference Systems
An efficient cluster head selection algorithm in wireless sensor networks is proposed in this paper. The implementation of the proposed algorithm can improve energy which allows the structured representation of a network topology. According to the residual energy, number of the neighbors, and the centrality of each node, the algorithm uses Fuzzy Inference Systems to select cluster head. The alg...
متن کاملLoad-Frequency Control: a GA based Bayesian Networks Multi-agent System
Bayesian Networks (BN) provides a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of load-frequency control (LFC). In practice, LFC systems use proportional-integral controllers. However since these controllers are designed using a linear model, the nonlinearities...
متن کاملOutlier Detection in Wireless Sensor Networks Using Distributed Principal Component Analysis
Detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (WSNs). To address the problem of outlier detection in wireless sensor networks, in this paper we present a PCA-based centralized approach and a DPCA-based distributed energy-efficient approach for detecting outliers in sensed data in a WSN. The outliers in sensed data can be ca...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2008