Differential evolution has proven itself a very simple while very powerful stochastic global optimizer. It has been applied to solve problems in many scientific and engineering fields.  Meer

This research book proposes a general conceptual framework for the development of automation in human-agents environments that will allow human- agent teams to work effectively and efficiently.  Meer

From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more.  Meer

“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation.  Meer

In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process.  Meer

From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more.  Meer

I ?rst met Jingqiao when he had just commenced his PhD research in evolutionary algorithms with Arthur Sanderson at Rensselaer. Jingqiao’s goals then were the investigation and development of a novel class of se- adaptivedi?  Meer

Agent based evolutionary search is an emerging paradigm in computational int- ligence offering the potential to conceptualize and solve a variety of complex problems such as currency trading, production planning, disaster response m- agement, business process management etc.  Meer

For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems.  Meer

This research book proposes a general conceptual framework for the development of automation in human-agents environments that will allow human- agent teams to work effectively and efficiently.  Meer

One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage.  Meer

Differential evolution has proven itself a very simple while very powerful stochastic global optimizer. It has been applied to solve problems in many scientific and engineering fields.  Meer

Civil engineering structures such as buildings, bridges, stadiums, and offshore structures play an import role in our daily life. However, constructing these structures requires lots of budget.  Meer

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents.  Meer

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents.  Meer

Civil engineering structures such as buildings, bridges, stadiums, and offshore structures play an import role in our daily life. However, constructing these structures requires lots of budget.  Meer

One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage.  Meer

Optimization is an integral part to science and engineering. Most real-world applications involve complex optimization processes, which are di?cult to solve without advanced computational tools.  Meer

Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling.  Meer

This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain learning in vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning.  Meer