Library of American University of Madaba
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Sarker, Ruhul Amin.
Agent-Based Evolutionary Search [electronic resource] / edited by Ruhul Amin Sarker, Tapabrata Ray. - 291p. 48 illus. in color. online resource. - Adaptation, Learning, and Optimization, 5 1867-4534 ; .
Agent Based Evolutionary Approach: An Introduction -- Multi-Agent Evolutionary Model for Global Numerical Optimization -- An Agent Based Evolutionary Approach for Nonlinear Optimization with Equality Constraints -- Multiagent-Based Approach for Risk Analysis in Mission Capability Planning -- Agent Based Evolutionary Dynamic Optimization -- Divide and Conquer in Coevolution: A Difficult Balancing Act -- Complex Emergent Behaviour from Evolutionary Spatial Animat Agents -- An Agent-Based Parallel Ant Algorithm with an Adaptive Migration Controller -- An Attempt to Stochastic Modeling of Memetic Systems -- Searching for the Effective Bidding Strategy Using Parameter Tuning in Genetic Algorithm -- PSO (Particle Swarm Optimization): One Method, Many Possible Applications -- VISPLORE: Exploring Particle Swarms by Visual Inspection.
The performance of Evolutionary Algorithms can be enhanced by integrating the concept of agents. Agents and Multi-agents can bring many interesting features which are beyond the scope of traditional evolutionary process and learning. This book presents the state-of-the art in the theory and practice of Agent Based Evolutionary Search and aims to increase the awareness on this effective technology. This includes novel frameworks, a convergence and complexity analysis, as well as real-world applications of Agent Based Evolutionary Search, a design of multi-agent architectures and a design of agent communication and learning Strategy.
9783642134258
Engineering.
Artificial intelligence.
Mathematics.
Engineering mathematics.
Engineering.
Appl.Mathematics/Computational Methods of Engineering.
Artificial Intelligence (incl. Robotics).
Applications of Mathematics.
519
Agent-Based Evolutionary Search [electronic resource] / edited by Ruhul Amin Sarker, Tapabrata Ray. - 291p. 48 illus. in color. online resource. - Adaptation, Learning, and Optimization, 5 1867-4534 ; .
Agent Based Evolutionary Approach: An Introduction -- Multi-Agent Evolutionary Model for Global Numerical Optimization -- An Agent Based Evolutionary Approach for Nonlinear Optimization with Equality Constraints -- Multiagent-Based Approach for Risk Analysis in Mission Capability Planning -- Agent Based Evolutionary Dynamic Optimization -- Divide and Conquer in Coevolution: A Difficult Balancing Act -- Complex Emergent Behaviour from Evolutionary Spatial Animat Agents -- An Agent-Based Parallel Ant Algorithm with an Adaptive Migration Controller -- An Attempt to Stochastic Modeling of Memetic Systems -- Searching for the Effective Bidding Strategy Using Parameter Tuning in Genetic Algorithm -- PSO (Particle Swarm Optimization): One Method, Many Possible Applications -- VISPLORE: Exploring Particle Swarms by Visual Inspection.
The performance of Evolutionary Algorithms can be enhanced by integrating the concept of agents. Agents and Multi-agents can bring many interesting features which are beyond the scope of traditional evolutionary process and learning. This book presents the state-of-the art in the theory and practice of Agent Based Evolutionary Search and aims to increase the awareness on this effective technology. This includes novel frameworks, a convergence and complexity analysis, as well as real-world applications of Agent Based Evolutionary Search, a design of multi-agent architectures and a design of agent communication and learning Strategy.
9783642134258
Engineering.
Artificial intelligence.
Mathematics.
Engineering mathematics.
Engineering.
Appl.Mathematics/Computational Methods of Engineering.
Artificial Intelligence (incl. Robotics).
Applications of Mathematics.
519