Efficient approximate inference in distributed Bayesian networks for MAS-based sensor interpretation
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 (Short Paper)
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 کاملDisTriB: Distributed Trust Management Model Based on Gossip Learning and Bayesian Networks in Collaborative Computing Systems
The interactions among peers in Peer-to-Peer systems as a distributed collaborative system are based on asynchronous and unreliable communications. Trust is an essential and facilitating component in these interactions specially in such uncertain environments. Various attacks are possible due to large-scale nature and openness of these systems that affects the trust. Peers has not enough inform...
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