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In this paper, we present a new fixed structure learning automaton (FSSA), called IJA, and study its steady state behavior in stationary environments. The proposed automaton characterizes by star shaped transition diagram and each branch of the star contains N states associated with a particular action. This new automaton is an improvement of the Krinsky(More)
In this paper, a new fixed structure learning automaton (FSSA), with a tuning parameter for amount of its rewards, is presented and its behavior in stationary environments will be studied. This new automaton is called TFSLA (tunable fixed structured learning automata). The proposed automaton characterizes by star shaped transition diagram and each branch of(More)
This paper presents a new approach based on artificial potential fields (APF) method which provides simple and effective motion planners for practical path planning in fully dynamic environments. We have exploited the fuzzy modeling to define fuzzy artificial potential fields (FAPF) which provides a real-time and flexible path planning, in contrast with(More)
The mobility model of typical mobile ad-hoc networks (MANET) can be used for more efficient performance evaluation of such networks. There are a large number of researches for generating various mobility models to use in performance evaluation of mobile ad-hoc networks and also on performance evaluation itself of these networks. But in most of these(More)
Soccer model and relation of players and coach has been analyzed by a learning automata-based method, called soccer mobility estimator (SME), who estimates the mobility model of soccer players. During a soccer match, players play according to a certain program designed by coach. The pattern of players' mobility is not stochastic and it can be assumed that(More)
This paper presents a new method for motion planning of mobile robots in dynamic environments based on wave expansion approach which avoids wave re-expansion in sudden obstacles case. Wave re-expansion in big scale environments takes considerable amount of time and process. A new wave expansion algorithm for path finding, either local minima or sudden(More)
This paper presents a new approach based on Artificial Potential Fields (APF) which provides real-time and very effective methodology for practical motion planners in unknown dynamic environments. The Maxwell's equations are exploited to define Artificial Magnetoquasistatic Fields (AMF) as an extension of APF, which provides a predictive, intelligent, and(More)
This paper utilizes IJA stochastic learning automaton for detecting noise and tuning value of alpha parameter which is used for image sharpening via gas diffusion model. The method has been applied to gray-scale images in an automatic and adaptive fashion. It is shown that the IJA automaton detects noise and can reform it appropriately. It glides the image(More)
In this paper we present a simulated annealingbased method for planning efficient paths with a tether which avoid entanglement in an obstacle-filled environment. By evaluating total path cost as a function of both path length and entanglements, a robot can plan a path through multiple points of interest while avoiding becoming entangled in any obstacle. In(More)