Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Book Part Citation - Scopus: 6Swarm and Entropic Modeling for Landmine Detection Robots(Springer Verlag, 2008) Bayram, Çağdaş; Sevil, Hakkı Erhan; Özdemir, SerhanEven at the dawn of the 21st century, landmines still pose a global threat. Buried just inches below the surface, combatants and noncombatants alike are all at risk of stepping on a mine. Their very nature is such that these furtive weapons do not discriminate, making it an urgent task to tackle the problem. According to the U.S.State Department [1], based on an estimate reported just a few years ago, there are well over 100 million anti-personnel mines around the world. The existence of these passive weapons causes a disruption in the development of already impoverished regions, as well as maiming or killing countless innocent passers-by. Since the ratification of the anti-personnel mine total ban treaty in 1997, their detection, removal, and elimination have become a top priority. Nevertheless, at the current rate, given the manpower and the man-hours that could be dedicated to the removal of these sleeping arms, it would take centuries. The concerns regarding the speed of removal and safety of the disposers eventually bring us to the discussion of the proposed method. Nature already provided good solutions to manage groups of less able beings: fish schools, ant swarms, animal packs, bird flocks, and so on.With the growing desire of humans to create intelligent systems, these biosystems are being thoroughly inspected [3-10] and implemented [11-14] in various studies. In this study a robotic agent is referred to as a drone, the group of robotic agents is referred to as a swarm, and the agent with mapping abilities is referred to as the alpha drone.Conference Object Citation - WoS: 4Citation - Scopus: 4A distributed behavioral model for landmine detection robots(International Association of Engineers, 2007) Bayram, Çağdaş; Sevil, Hakkı Erhan; Özdemir, SerhanThis paper presents a distributed navigation, detection and swarming model for a group of minimalist identical robotic agents. Decision making process of agents is weight based in contrast to widely used precedence based rules. The group is indirectly controlled by an alpha agent that has more sophisticated systems. Computer simulations of the proposed behavioral model generated promising results.Conference Object Citation - Scopus: 1The Effects of Bias, Population Migration and Credit Assignment in Optimizing Trait-Based Heterogeneous Populations(CSREA Press, 2005) Gezgin, Erkin; Sevil, Hakkı Erhan; Özdemir, SerhanPopulation based search algorithms are becoming the mainstay in nonlinear problems with discontinuous search domains. The generic name of genetic algorithms (GAs) basicly applies to all population based methods. GAs have spawned many versions to suit new applications. Some of these alterations have reached such points that the algorithms may no longer be called GAs. One similar study may be found in [1], in which a perturbation based search algorithm was proposed, called Responsive Perturbation Algorithm (RPA). In a later work [2], instead of a population of homogenous individuals, as is the case for generic GAs, a population of heterogeneous individuals has been set to compete. Replacing the set of winner parents, the fittest individual is made the parent to yield offspring. The current work is now called, with the supplements, trait-based heterogeneous populations plus (TbHP+). Credit assignment and bias concepts in the form of immunity and instinct has been added to provide the populations with a more efficient guidance. Simulations were made through an RBF neural network training, as it was carried out in earlier works, mentioned above, for comparison. Results were prsented at the end as network testing errors which showed further improvement with TbHP+.