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The cellular learning automaton (CLA), which is a combination of cellular automaton (CA) and learning automaton (LA), is introduced recently. This model is superior to CA because of its ability to learn and is also superior to single LA because it is a collection of LAs which can interact with each other. The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA...
The minimum connected dominating set (MCDS) of a given graph G is the smallest sub-graph of G such that every vertex in G belongs either to the sub-graph or is adjacent to a vertex of the sub-graph. Finding the MCDS in an arbitrary graph is a NP-Hard problem, and several approximation algorithms have been proposed for solving this problem in deterministic graphs, but to the best of our knowledge no...
Learning automata (LA) is an abstract model which can be used to guide action selection at any stage of a system by past actions and environment responses to improve some overall performance function. The use of intelligent algorithms based on learning automata can be efficient for traffic control. However, these learning schemes have been focused only to unimodal routing problem in connection oriented...
Clustering is currently one of the most crucial techniques for dealing with massive amount of heterogeneous information on the web, which is beyond human beingpsilas capacity to digest. Recent studies have shown that the most commonly used partitioning-based clustering algorithm, the K-means algorithm, is more suitable for large datasets. However, the K-means algorithm can generate a local optimal...
This paper presents a reliable decentralized mutual exclusion algorithm for distributed systems in which processes communicate by asynchronous message passing. When any failure happens in system, the algorithm protects the distributed system against any crash. It also makes possible the recovery of lost data in system. It requires between (N-1) and 2(N-1) messages per critical section access, where...
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