Ant Colony Book

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Ant Colony

By Michael DeForge
  • ISBN Code: : UCSD:31822040877516
  • Publisher : Drawn and Quarterly
  • Pages : 112
  • Category : Comics & Graphic Novels
  • Reads : 752
  • Book Compatibility : Pdf, ePub, Mobi, Kindle
  • Pdf : ant-colony.pdf

Book Excerpt :

Follows the strange exploits of a handful of black ants in a colony at war with a nearby colony of red ants.

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Read Also This Books

Inside an Ant Colony

By Greg Roza
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : The Rosen Publishing Group, Inc
  • Book Code : 9781448837007
  • Total of Pages : 16
  • Category : Juvenile Nonfiction
  • Members : 190
  • Pdf File: inside-an-ant-colony.pdf

Book Short Summary:

If a second-grader was a strong as an ant, he or she would be able to lift a car. This book takes readers under the surface into the fascinating and complex world of the ant colony. Books of the Real Life Readers Program use real life scenario narratives to help readers further develop content-area reading, writing, and comprehension skills.

Ant Colony Optimization and Constraint Programming

By Christine Solnon
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : John Wiley & Sons
  • Book Code : 9781118618899
  • Total of Pages : 320
  • Category : Computers
  • Members : 865
  • Pdf File: ant-colony-optimization-and-constraint-programming.pdf

Book Short Summary:

Ant colony optimization is a metaheuristic which has beensuccessfully applied to a wide range of combinatorial optimizationproblems. The author describes this metaheuristic and studies itsefficiency for solving some hard combinatorial problems, with aspecific focus on constraint programming. The text is organizedinto three parts. The first part introduces constraint programming, which provideshigh level features to declaratively model problems by means ofconstraints. It describes the main existing approaches for solvingconstraint satisfaction problems, including complete tree searchapproaches and metaheuristics, and shows how they can be integratedwithin constraint programming languages. The second part describes the ant colony optimizationmetaheuristic and illustrates its capabilities on differentconstraint satisfaction problems. The third part shows how the ant colony may be integrated within aconstraint programming language, thus combining the expressivepower of constraint programming languages, to describe problems ina declarative way, and the solving power of ant colony optimizationto efficiently solve these problems.

Ant Colony Optimization and Applications

By Stefka Fidanova
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Springer Nature
  • Book Code : 9783030673802
  • Total of Pages : 125
  • Category : Technology & Engineering
  • Members : 412
  • Pdf File: ant-colony-optimization-and-applications.pdf

Book Short Summary:

This book is interesting and full of new ideas. It provokes the curiosity of the readers. The book targets both researchers and practitioners. The students and the researchers will acquire knowledge about ant colony optimization and its possible applications as well as practitioners will find new ideas and solutions of their combinatorial optimization and decision-making problems. Ant colony optimization is between the best method for solving difficult optimization problems arising in real life and industry. It has obtained distinguished results on some applications with very restrictive constraints. The reader will find theoretical aspects of ant method as well as applications on a variety of problems. The following applications could be mentioned: multiple knapsack problem, which is an important economical problem; grid scheduling problem; GPS surveying problem; E. coli cultivation modeling; wireless sensor network positioning; image edges detection; workforce planning.

Decision Tree and Ensemble Learning Based on Ant Colony Optimization

By Jan Kozak
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Springer
  • Book Code : 9783319937526
  • Total of Pages : 159
  • Category : Technology & Engineering
  • Members : 416
  • Pdf File: decision-tree-and-ensemble-learning-based-on-ant-colony-optimization.pdf

Book Short Summary:

This book not only discusses the important topics in the area of machine learning and combinatorial optimization, it also combines them into one. This was decisive for choosing the material to be included in the book and determining its order of presentation. Decision trees are a popular method of classification as well as of knowledge representation. At the same time, they are easy to implement as the building blocks of an ensemble of classifiers. Admittedly, however, the task of constructing a near-optimal decision tree is a very complex process. The good results typically achieved by the ant colony optimization algorithms when dealing with combinatorial optimization problems suggest the possibility of also using that approach for effectively constructing decision trees. The underlying rationale is that both problem classes can be presented as graphs. This fact leads to option of considering a larger spectrum of solutions than those based on the heuristic. Moreover, ant colony optimization algorithms can be used to advantage when building ensembles of classifiers. This book is a combination of a research monograph and a textbook. It can be used in graduate courses, but is also of interest to researchers, both specialists in machine learning and those applying machine learning methods to cope with problems from any field of R&D.

An Ant's Colony

By Erika de Nijs
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Cavendish Square Publishing, LLC
  • Book Code : 9781502620750
  • Total of Pages : 24
  • Category : Juvenile Nonfiction
  • Members : 428
  • Pdf File: an-ant-s-colony.pdf

Book Short Summary:

These muscular members of the insect world are capable of moving large objects, whether food or building material, in an organized and cooperative fashion. This book provides a view of the layout of a belowground colony and looks at the different environments that various species of ants call home.

Ant Colony Optimization Algorithm for Load Balancing in Grid Computing UUM Press

By Ku Ruhana Ku Mahamud
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : UUM Press
  • Book Code : 9789670474090
  • Total of Pages : 72
  • Category : Computers
  • Members : 687
  • Pdf File: ant-colony-optimization-algorithm-for-load-balancing-in-grid-computing-uum-press.pdf

Book Short Summary:

Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources. This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. The proposed algorithm is known as the enhance Ant Colony Optimization (EACO). The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism. The resource allocation problem is modelled as a graph that can be used by the ant to deliver its pheromone. This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element. The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job. EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form. The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job. Resources with high pheromone value are selected to process the submitted jobs. Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization. Experimental results show that EACO produced better grid resource management solution.