Ant Colonies : Behavior in Insects and Computer Applications.

Intro -- ANT COLONIES: BEHAVIOR IN INSECTS AND COMPUTER APPLICATIONS -- ANT COLONIES: BEHAVIOR IN INSECTS AND COMPUTER APPLICATIONS -- CONTENTS -- PREFACE -- Chapter 1 PROGRESSIVE ORGANIZATION OF CO-OPERATING COLONIES/COLLECTIONS OF ANTS/AGENTS (POOCA) FOR COMPETENT PHEROMONE-BASED NAVIGATION AND MULTI-AGENT LEARNING -- Abstract -- 1. Introduction -- 2. Robot Navigation -- 3. Real Ants Colonies - Ant-Inspired Navigation and Optimization -- 3.1. Ant Foraging - Stigmetry -- 3.1.1. Independent navigation employing long-term memory -- 3.1.2. Cooperative navigation and pheromone trail following -- 3.2. Ant-Inspired Navigation - Ant Colony Optimization - Multi-Agent Systems - Swarm Robotics -- 3.2.1. Swarm intelligence and ant colony optimization - Swarm robotics -- 3.2.2. Co-Operative multi agent systems -- 4. Progressive Optimization of Organized Colonies of Ants (POOCA) -- 4.1. POOCA Principles -- 4.2. POOCA Problem Representation -- 4.3. POOCA Operation -- 4.4. POOCA Trail Optimization via Evolution -- 5. Navigation Problems -- 5.1. Static Problems -- 5.1.1. Obstacle-free navigation -- 5.1.2. Navigation in environments cluttered with obstacles -- 5.2. Dynamic Environments -- 6. Future Research -- 7. Conclusion -- Acknowledgments -- Dedication -- References -- Chapter 2 ANT COLONY SOLUTION TO THE OPTIMAL TRANSFORMER SIZING AND EFFICIENCY PROBLEM IN POWER SYSTEMS -- Abstract -- 1. Introduction -- 2. Overview of the Proposed Method -- 2.1. Optimal Transformer Sizing -- 2.2. Optimal Transformer Efficiency Selection -- 3. Calculation of Transformer Thermal Loading -- 3.1. Top-Oil Temperature Calculation -- 3.2. Winding Hottest Spot Temperature Calculation -- 3.3. Insulation Aging -- 3.4. Overloading Capability -- 4. Calculation of Transformer Energy Loss Cost -- 5. Elitist Ant System Method -- 5.1. Mechanism of EAS Algorithm.

5.2. OTS Implementation Using the EAS Algorithm -- 6. Application of ACO Algorithm to Optimal Transformer Sizing Problem -- 7. Application of ACO Algorithm to Optimal Transformer Efficiency Selection Problem -- 8. Implementation of ACO Algorithm in Matlab -- 9. Conclusions -- References -- Chapter 3 DISTRIBUTED DECISIONS: NEW INSIGHTS FROM RADIO-TAGGED ANTS -- Abstract -- Introduction -- Distributed Decisions: Ants as a Model System -- The Role of RFID Technology -- Methodology -- RFID Technology -- Application to Ants -- Distributed Decisions -- Case Study 1: Task-Allocation -- Case Study 2: Nest Choice and Emigration -- Conclusion -- Future Directions -- Distributed Decisions -- Acknowledgments -- References -- Chapter 4 IMPACTS, ECOLOGY AND DISPERSAL OF THE INVASIVE ARGENTINE ANT -- Abstract -- Introduction -- The Argentine Ant Linepithema Humile: Pest Status -- Distribution and Habitat -- Impacts -- 1) Impacts on Ecosystems -- 2) Impacts on Agriculture -- 3) Impacts in Urban Area -- Ecology -- 1) Polygyny [Multi-Queen System] -- 2) Colony Budding -- 3) Opportunistic Nesting Behavior -- 4) Supercoloniality -- 5) Broad Dietary Spectrum -- Control -- Dispersal -- Means of Dispersal -- Keys to Infer Dispersal History of Argentine Ants: Relevance of Supercolony Identity -- Dispersal History -- Conclusion -- Acknowledgments -- References -- Chapter 5 ANT COLONY OPTIMIZATION USED IN NO WAVEFRONT SENSOR ADAPTIVE OPTICS SYSTEMS FOR SOLID-STATE LASERS -- Abstract -- 1. Introduction -- 2. Ant Colony Algorithm -- 4. Simulations and Results -- 5. Conclusion -- References -- Chapter6ANTCOLONYOPTIMIZATIONAGENTSANDPATHROUTING:THECASESOFCONSTRUCTIONSCHEDULINGANDURBANWATERDISTRIBUTIONPIPENETWORKS -- Abstract -- 1.Introduction -- 2.AntColonyOptimization -- 2.1.TheACOMetaheuristic -- 3.CaseStudy1:Resource-UnconstrainedConstructionScheduling.

3.1.ACO-basedAlgorithm -- 3.2.ConstructionProjectExample -- 3.2.1.TheACOApproach -- 4.CaseStudy2:RoutingofPipingNetworks -- 4.1.ACO-BasedAlgorithm -- 4.2.AMoreComplicatedCaseStudy -- 4.2.1.ACO-BasedSolution -- 5.ComparingACOwithotherPathSearchTechniques -- 6.Conclusion -- References -- Chapter7KANTS:ASELF-ORGANIZEDANTSYSTEMFORPATTERNCLUSTERINGANDCLASSIFICATION -- Abstract -- 1.Introduction -- 2.PreliminaryConcepts -- 2.1.ACO -- 2.2.SOM -- 2.3.AntSystemModel -- 3.Self-OrganizingAntsModel -- 3.1.DecideWheretoGoRule -- 3.2.TheUpdatingFunction -- 3.3.TheEvaporationFunction -- 3.4.Pseudocode -- 4.ExperimentsandResults -- 4.1.TheDatasets -- 4.2.Clustering -- 4.3.Classification -- 5.Conclusion -- References -- Chapter8AHYBRIDSYSTEMBASEDINANTCOLONYANDPARACONSISTENTLOGIC -- Abstract -- 1.Introduction -- 2.AntColonyOptimization -- 2.1.CombinatorialOptimizationProblems -- 2.1.1.HeuristicAlgorithms -- Metaheuristics -- 2.2.BiologicalInspiration -- 2.3.Pseudo-codeoftheACOMetaheuristic -- 2.3.1.TheConstructionofSolutionsbyAnts -- 2.3.2.UpdatingthePheromone -- 2.3.3.VariationsoftheACOMetaheuristic -- 3.ParaconsistentLogic -- 3.1.ClassicalLogic -- 3.2.Non-classicalLogic -- 3.3.HistoryofParaconsistentLogic -- 3.4.FoundationsofParaconsistentLogic -- ParaconsistentLogicModelingHumanKnowledge -- 3.4.1.PropositionalParaconsistentAnnotatedLogicP˝ -- 3.4.2.RepresentationofLatticesofAnnotatedParaconsistentLogic -- 3.4.3.ParaconsistentAnnotatedLogicwithAnnotationofTwoValuesPAL2v -- 3.4.4.AnotherInterpretationofPAL2v -- 3.4.5.TheExtentoftheParaconsistentAnnotatedLogicofThreeVariables -- 4.HybridSystem=PAL+ACO -- 4.1.ExperimentalResults -- 5.Conclusion -- References -- Chapter 9 ANT COLONY OPTIMIZATION: A POWERFUL STRATEGY FOR BIOMARKER FEATURE SELECTION* -- Abstract -- Introduction -- Conclusion -- Acknowledgments -- References.

Chapter 10 ANT COLONY OPTIMIZATION BASED MESSAGE AUTHENTICATION FOR WIRELESS NETWORKS* -- Abstract -- 1. Introduction -- 2. Cellular Network System -- 3. Ant Colony Optimization -- 4. System Model and Key Distribution Scheme -- 5. Mark Generation in Packets Using Ant Colony Optimization Based Boolean Function Minimization -- 5.1. Model of an Ant System -- 6. ABXE Algorithm-Construction and Design -- 6.1. Ant Agent Representation of the Boolean Expression -- Assignment of Energy Value -- Computation of Energy Value for a Large Number of Packets in a Group -- 6.4. Algorithm: Ant Colony Optimized Boolean Expression Evolver -- 6.4. Algorithm: Ant Colony Optimized Boolean Expression Evolver -- 7. Experimental Results -- 8. Comparison with Existing Methods -- 8.1. Merkle Tree Approach -- 8.2. ACO Based Message Authentication -- 9. Conclusion -- Acknowledgment -- References -- INDEX -- Blank Page.

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