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Urban cities are getting more congested with vehicular traffic and most of the traffic control systems are not smart to detect and give priority to emergency vehicles. The effect results to inadequate services delivered by the public emergency agencies, and unnecessary traffic congestion to other road users at intersection points. In this paper we present an effective reinforced road traffic control...
Reliability, interoperability and efficiency are fundamental in Wireless Sensor Network deployment. Herein we look at how transmission power control may be used to reduce interference, which is particularly problematic in high-density conditions. We adopt a distributed approach where every node has the ability to learn which transmission power is most appropriate, given the network conditions and...
There are several groups of routing algorithms in dynamically changing networks developing every year. We introduce an additional parameter “Battery Life decrease” in the existing Q-Routing protocol. The Battery Life is reduced in direct proportion to the number of packets transmitted to the node. The efficiency of the Optimized Battery Life Q-Routing protocol is estimated by total loss of network...
Construction of learning structures for Bayesian networks is considered in this work when data is securely maintained by different parties, not willing to reveal their individual private data to each other. We propose a privacy-preserving protocol for Bayesian network from data which is homogeneously partitioned among two or more parties by using K2 algorithm, a heuristic algorithm typically used...
As the world market is becoming increasingly dynamic and intense, manufacturing enterprises require responsive manufacturing systems which having ability to response rapidly to dynamic changes, to satisfied customer needs. Multi-agent system is used to model manufacturing system in this paper. A multi-agent system based system architecture for agile manufacturing systems which include agent architectures,...
Recently, traffic classification (TC) becomes more and more important for network management and measurement tasks. The new-coming machine learning based classification methods can achieve high classification accuracy and fast identification ability; however, all these related TC methods up to now always have the assumption of the stability of classification model constituted from network traffic...
At present, applying machine learning theory to the multi-agent automatic negotiation system has become the latest research focus in e-commerce area. The paper aimed at using Bayesian rules to update the environmental information in negotiation, using the Q-learning algorithm of reinforcement-learning to generate the negotiation proposals, and established a multi-agent automatic negotiation model...
With the rapid development of multi-agent based E-commerce systems, on-line automatic negotiation protocol is often needed. But because of incomplete information agents have, the efficiency of on-line negotiation protocol is rather low. To overcome the problem, an on-line agent bilateral multi-issue alternate bidding negotiation protocol based on reinforcement learning is present. The reinforcement...
Network traffic policy verification is the analysis of network traffic to determine if the observed traffic is in compliance or violation of the applied policy. An intuitive approach is the use of machine learning techniques based on specific network traffic characteristics. These traffic characteristics are also known as features, which have to be extracted and selected carefully to build robust...
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