Decision Space

Looks at the critical role of community members and other interested parties in environmental policy decision making.

This book constitutes the refereed proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005, held in Guanajuato, Mexico, in March 2005. The 59 revised full papers presented together with 2 invited papers and the summary of a tutorial were carefully reviewed and selected from the 115 papers submitted. The papers are organized in topical sections on algorithm improvements, incorporation of preferences, performance analysis and comparison, uncertainty and noise, alternative methods, and applications in a broad variety of fields.

Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience. Complete information is not always available—or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm—creating new learning applications and, ultimately, more intelligent machines. The first book of its kind in this new and growing field, Reinforcement and Systemic Machine Learning for Decision Making focuses on the specialized research area of machine learning and systemic machine learning. It addresses reinforcement learning and its applications, incremental machine learning, repetitive failure-correction mechanisms, and multiperspective decision making. Chapters include: Introduction to Reinforcement and Systemic Machine Learning Fundamentals of Whole-System, Systemic, and Multiperspective Machine Learning Systemic Machine Learning and Model Inference and Information Integration Adaptive Learning Incremental Learning and Knowledge Representation Knowledge Augmentation: A Machine Learning Perspective Building a Learning System With the potential of this paradigm to become one of the more utilized in its field, professionals in the area of machine and systemic learning will find this book to be a valuable resource.

Marketing often scares entrepreneurs. They've sweat buckets coming up with a valuable product or service, and now they have to sell it? Won't it sell itself? No. But, as marketing expert Bob Everett shows, marketing is just not that hard. At some level, entrepreneurs know that. They know what appeals to them and what leaves them cold. They know when a person or marketing claim is trustworthy, and they know when claims are exaggerated. Yet when it comes to marketing their own products and services to others, entrepreneurs often find it difficult to apply that same judgment and common sense. Everett to the rescue! He helps entrepreneurs position products in the market, then sell them effectively and ethically. Everett first destroys marketing myths: • Marketing is difficult and needs to be done by professionals. • Good marketing has to be expensive. • Marketing skills require extensive training • Marketing requires a great deal of creativity These myths have spawned a multi-billion dollar industry consisting of advertising agencies, public relations firms, marketing consultants, and academic marketing programs in business schools. But as this book shows, marketing is a simple process that anyone can master—and that entrepreneurs must master if they are to succeed. Fortunately, the most effective marketing programs are usually the most honest, simple, and inexpensive. The Entrepreneur's Guide to Marketing is designed to help the entrepreneur, business owner, manager, or marketing professional harness his or her own inner wisdom and personal experience to develop powerful and efficient marketing programs. Both a how-to and a how to think about it book, it takes readers through a step-by-step process of figuring things out for themselves. The result? A successful marketing program that will help entrepreneurs harvest new customers, more dollars, and overall success.

This volume brings together important new research in decision science, capturing the crucial role of local context in a globalized, standardized world. Assembling the best work presented at the 2013 Conference of the European Decision Sciences Institute, it considers classic decision science problems from a new perspective, offering insights for improving decision-making in government, business, healthcare, education, manufacturing, the military, and beyond. The papers in Common Disciplines that Separate Us embrace the duality of globally determined local contexts, offering new approaches to decision-making related to: Strengthening national economic competitiveness Reforming the public sector and higher education Deploying information technology more effectively throughout government Making healthcare policy that achieves better outcomes at lower cost Analyzing social networks Improving processes via data visualization, modeling, and simulation Gaining more value from enterprise business intelligence Offshoring, nearshoring, "right shoring," and other key manufacturing decisions Improving supply chain performance And much more The papers collected here will be valuable to wide audiences of faculty, researchers, and students in diverse programs covering business, public administration, and economics; and for others interested in the frontiers of decision science.

Presents information to create a trade-off analysis framework for use in government and commercial acquisition environments This book presents a decision management process based on decision theory and cost analysis best practices aligned with the ISO/IEC 15288, the Systems Engineering Handbook, and the Systems Engineering Body of Knowledge. It provides a sound trade-off analysis framework to generate the tradespace and evaluate value and risk to support system decision-making throughout the life cycle. Trade-off analysis and risk analysis techniques are examined. The authors present an integrated value trade-off and risk analysis framework based on decision theory. These trade-off analysis concepts are illustrated in the different life cycle stages using multiple examples from defense and commercial domains. Provides techniques to identify and structure stakeholder objectives and creative, doable alternatives Presents the advantages and disadvantages of tradespace creation and exploration techniques for trade-off analysis of concepts, architectures, design, operations, and retirement Covers the sources of uncertainty in the system life cycle and examines how to identify, assess, and model uncertainty using probability Illustrates how to perform a trade-off analysis using the INCOSE Decision Management Process using both deterministic and probabilistic techniques Trade-off Analytics: Creating and Exploring the System Tradespace is written for upper undergraduate students and graduate students studying systems design, systems engineering, industrial engineering and engineering management. This book also serves as a resource for practicing systems designers, systems engineers, project managers, and engineering managers. Gregory S. Parnell, PhD, is a Research Professor in the Department of Industrial Engineering at the University of Arkansas. He is also a senior principal with Innovative Decisions, Inc., a decision and risk analysis firm and has served as Chairman of the Board. Dr. Parnell has published more than 100 papers and book chapters and was lead editor of Decision Making for Systems Engineering and Management, Wiley Series in Systems Engineering (2nd Ed, Wiley 2011) and lead author of the Handbook of Decision Analysis (Wiley 2013). He is a fellow of INFORMS, the INCOSE, MORS, and the Society for Decision Professionals.

Healthcare Delivery Reform and New Technologies: Organizational Initiatives contains cross-disciplinary research on strategic initiatives for healthcare reform that impact not only patients, but also organizations, healthcare providers, and policymakers. Contributions focus on the operational as well as theoretical aspects of healthcare management, healthcare delivery processes, and patient-centered initiatives.