Thinking In Complexity

Complexity and nonlinearity are prominent features in the evolution of matter, life, and human society. Even our mind seems to be governed by the nonlinear dynamics of the complex networks in our brain. This book considers complex systems in the physical and biological sciences, cognitive and computer sciences, social and economic sciences, and philosophy and history of science. An in terdisciplinary methodology is introduced to explain the emergence of order in nature and mind and in the econ omy and society by common principles. These methods are sometimes said to foreshadow the new sciences of complexity characterizing the scientific deve10pment of the 21 st century. The book critically an alyzes the successes and limits of this approach, its sys tematic foundations, and its historical and philosophical background. An epilogue discusses new standards of eth ical behavior which are demanded by the complex prob lems of nature and mind, economy and society.

This new edition also treats smart materials and artificial life. A new chapter on information and computational dynamics takes up many recent discussions in the community.

Dive into Python's advanced possibilities, including algorithm analysis, graphs, scale-free networks, and cellular automata with this in-depth, hands-on guide.

The underlying idea and motive for the book is that the notion of complexity may humanize the social sciences, may conceive the complex human being as more human, and turn reality as assumed in our doing social science into a more complex, that is a richer reality for all. The main focus of this book is on new thinking in complexity, with complexity to be taken as derived from the Latin word complexus: ‘that which is interwoven.’ The trans-disciplinary approach advocated here will be trans-disciplinary in two ways: firstly, by going beyond the separate disciplines within the fields of both natural sciences and social sciences, and, secondly, by going beyond the separate cultures of the natural sciences and of the social sciences and humanities.

Systems Thinking, Third Edition combines systems theory and interactive design to provide an operational methodology for defining problems and designing solutions in an environment increasingly characterized by chaos and complexity. This new edition has been updated to include all new chapters on self-organizing systems as well as holistic, operational, and design thinking. The book covers recent crises in financial systems and job markets, the housing bubble, and environment, assessing their impact on systems thinking. A companion website is available at interactdesign.com. This volume is ideal for senior executives as well as for chief information/operating officers and other executives charged with systems management and process improvement. It may also be a helpful resource for IT/MBA students and academics. Four NEW chapters on self-organizing systems, holistic thinking, operational thinking, and design thinking Covers the recent crises in financial systems and job markets globally, the housing bubble, and the environment, assessing their impact on systems thinking Companion website to accompany the book is available at interactdesign.com

The world has become increasingly networked and unpredictable. Decision makers at all levels are required to manage the consequences of complexity every day. They must deal with problems that arise unexpectedly, generate uncertainty, are characterised by interconnectivity, and spread across traditional boundaries. Simple solutions to complex problems are usually inadequate and risk exacerbating the original issues. Leaders of international bodies such as the UN, OECD, UNESCO and WHO — and of major business, public sector, charitable, and professional organizations — have all declared that systems thinking is an essential leadership skill for managing the complexity of the economic, social and environmental issues that confront decision makers. Systems thinking must be implemented more generally, and on a wider scale, to address these issues. An evaluation of different systems methodologies suggests that they concentrate on different aspects of complexity. To be in the best position to deal with complexity, decision makers must understand the strengths and weaknesses of the various approaches and learn how to employ them in combination. This is called critical systems thinking. Making use of over 25 case studies, the book offers an account of the development of systems thinking and of major efforts to apply the approach in real-world interventions. Further, it encourages the widespread use of critical systems practice as a means of ensuring responsible leadership in a complex world. Comments on a previous version of the book: Russ Ackoff: ‘the book is the best overview of the field I have seen’ JP van Gigch: ‘Jackson does a masterful job. The book is lucid ...well written and eminently readable’ Professional Manager (Journal of the Chartered Management Institute): ‘Provides an excellent guide and introduction to systems thinking for students of management’

Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you’ll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics. Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations. In this updated second edition, you will: Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.

This research monograph describes a new approach to the measurement of thinking processes. The author begins with a discussion of the logic of thought versus the psychology of thinking. Traditionally, thinking has been defined in terms of the logical thought processes which lead to warranted conclusions. The psychological processes, on the other hand, involve the individual's perceptions, intentions and information-processing strategies. Traditional logical approaches appear to be most suitable for analysis of thinking in "formal" highly structured problem situations. Current tests of critical thinking reflect the "logical" approaches to measuring thinking; two tests of this type are evaluated by the author. The authors define the information-processing approach to measurement of thinking, which emphasizes the way situational information is perceived, selected, organized and interpreted. Using this approach, the authors have developed two interpretive exercises, The Holocaust and The Bomb Factories. The results of a number of studies conducted with these exercises are presented, and future work is projected.