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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...
In this paper, we propose some learning automata-based algorithms to solve the minimum spanning tree problem in stochastic graphs when the probability distribution function of the edge's weight is unknown. In these algorithms, at each stage a set of learning automata determines which edges to be sampled. This sampling method may result in decreasing unnecessary samples and hence decreasing the running...
The vertex coloring problem is a well-known classical problem in graph theory in which a color is assigned to each vertex of the graph such that no two adjacent vertices have the same color. The minimum vertex coloring problem is known to be an NP-hard problem in an arbitrary graph, and a host of approximation solutions are available. In this paper,four learning automata-based approximation algorithms...
Finding an efficient route is difficult problem for many drivers. Car Navigation Systems are sometimes offered as a special feature on new cars. These systems are capable of performing some of the tasks traditionally performed by driver, such as determining the best route to the destination. This process of finding shortest path from one point to another, is called routing. In this paper, a new shortest...
Multi-agent Markov decision processes (MMDPs) are widely used for modeling many types of multi-agent systems. In this paper, two new algorithms based on learning automata are proposed for solving MMDPs and finding optimal policies. In the proposed algorithms, Markov problem is described as a directed graph. The nodes of this graph are the states of the problem, and the directed edges represent the...
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