2010 Conference Abstracts: Annual Undergraduate Research Conference at the Interface of Biology and Mathematics

Abstract book for the Second Annual Undergraduate Research Conference at the Interface of Biology and Mathematics Date: November 19 - 20, 2010Plenary speaker: Abdul-Aziz Yakubu, Professor and Chair of the Department of Mathematics, Howard UniversityFeatured speaker: Jory Weintraub, Assistant Director Education and Outreach, National Evolutionary Synthesis Cente

Sustainable Industrial Engineering along Product-Service Life Cycle/Supply Chain

Sustainable industrial engineering addresses the sustainability issue from economic, environmental, and social points of view. Its application fields are the whole value chain and lifecycle of products/services, from the development to the end-of-life stages. This book aims to address many of the challenges faced by industrial organizations and supply chains to become more sustainable through reinventing their processes and practices, by continuously incorporating sustainability guidelines and practices in their decisions, such as circular economy, collaboration with suppliers and customers, using information technologies and systems, tracking their products’ life-cycle, using optimization methods to reduce resource use, and to apply new management paradigms to help mitigate many of the wastes that exist across organizations and supply chains. This book will be of interest to the fast-growing body of academics studying and researching sustainability, as well as to industry managers involved in sustainability management

Agent-Based Models and Human Subject Experiments

This paper considers the relationship between agent-based modeling and economic decision-making experiments with human subjects. Both approaches exploit controlled ``laboratory'' conditions as a means of isolating the sources of aggregate phenomena. Research findings from laboratory studies of human subject behavior have inspired studies using artificial agents in ``computational laboratories'' and vice versa. In certain cases, both methods have been used to examine the same phenomenon. The focus of this paper is on the empirical validity of agent-based modeling approaches in terms of explaining data from human subject experiments. We also point out synergies between the two methodologies that have been exploited as well as promising new possibilities.agent-based models, human subject experiments, zero- intelligence agents, learning, evolutionary algorithms

Handbook of Computational Intelligence in Manufacturing and Production Management

Artificial intelligence (AI) is simply a way of providing a computer or a machine to think intelligently like human beings. Since human intelligence is a complex abstraction, scientists have only recently began to understand and make certain assumptions on how people think and to apply these assumptions in order to design AI programs. It is a vast knowledge base discipline that covers reasoning, machine learning, planning, intelligent search, and perception building. Traditional AI had the limitations to meet the increasing demand of search, optimization, and machine learning in the areas of large, biological, and commercial database information systems and management of factory automation for different industries such as power, automobile, aerospace, and chemical plants. The drawbacks of classical AI became more pronounced due to successive failures of the decade long Japanese project on fifth generation computing machines. The limitation of traditional AI gave rise to development of new computational methods in various applications of engineering and management problems. As a result, these computational techniques emerged as a new discipline called computational intelligence (CI)

Law\u27s Complexity: A Primer

The legal system. It rolls easily off the tongues of lawyers like a single word - the legal system - as if we all know what it means. But what is the legal system? How does it behave? What are its boundaries? What is its input and output? How will it look in one year? In ten years? How should we use it to make change in some other aspect of social life? Why do answers to these questions make the legal system seem so complex? Would assembling a cogent, descriptively accurate theory of what makes the legal system complex help us to formulate more accurate and useful propositions about the legal system? I have to believe it would, and in my pursuit of such an explanation I have leaned heavily on the theory of complex adaptive systems - the study of systems comprised of a macroscopic, heterogeneous set of autonomous agents interacting and adapting in response to one another and to external environment inputs. At its deepest level, complex adaptive systems theory as applied to the legal system presents a rich and dynamic field of study. It asks whether the targets of law are complex adaptive systems, and if so what that means for law\u27s design. It asks whether law itself, however we define its boundaries, is also a complex adaptive system, and if so what that means for law\u27s design. And it asks how law and its regulatory targets co-evolve and what that means for law\u27s design. This article orients those three questions within the context of complex adaptive systems theory. Part I provides a short primer on complex adaptive systems theory and suggests ways of usefully mapping it onto the legal system to expand our understanding of its behavior and properties. To make the case for the practical utility complex adaptive systems theory has for law, Part II explores a few of the major implications the theoretical foundation has for institutional and instrument design issues in law. I close by offering suggestions for next steps in the development of the theory of law\u27s complexity

Tradition and Innovation in Construction Project Management

This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings