1. Spring 2010 - ÇGIE 398 - lecture 41 lecture 4: complexity simple systems, complex systems –parallel developments that are joining together: systems literature complexity literature –most systems of interest to IE/OR are complex –to understand the causes that gave rise to these developments we need to understand how science and the scientific method work

2. Spring 2010 - ÇGIE 398 - lecture 42 science and the scientific method ways to knowledge: – authoritarian and mystical mode versus the rational mode – the Enlightenment, Galileo and Newton – Newtonian mechanics aims of science – seeking reality and truth – explanation – prediction – understanding the scientific method - positivism – objectivity – the research cycle: theory-hypothesis-observation and experimentation-generalisation-theory

3. Spring 2010 - ÇGIE 398 - lecture 43 calculus and analytic functions – analysis – reduction the Newtonian paradigm – objective knowledge is possible – cause and effect act linearly – nature is deterministic or predictable – reduction works Newtonian science has been a great success; it has created today’s technological society the Newtonian view of the world dominates our thinking even today

4. Spring 2010 - ÇGIE 398 - lecture 44 complexity quantum mechanics and relativity insufficiency of analytical thinking in the study of living organisms that must import energy failure of calculus in studying complex shapes realisation that nature is more complex than previously thought led to the development of the new field of complexity studies. complexity theory is as yet not fully developed its aim is to discover unified laws governing complex systems through interdisciplinary inquiry it is early to say whether this aim will be achieved

5. Spring 2010 - ÇGIE 398 - lecture 45 concepts of complexity nonlinear dynamics – the two-body and the three-body problems – chaotic behaviour the butterfly effect glasses, mountains, earthquakes etc. – thermodynamic equilibrium – maximum entropy environment – boundary setting and closure – separation of scales – e.g. the molecular motion of air – the impossibility of the separation of scales – environmental fallacy

6. Spring 2010 - ÇGIE 398 - lecture 46 emergence – emergence is the fundamental property of systems – examples of emergence – emergent behaviour at a higher level of scale arises from lower levels of scale although the mechanisms involved are difficult to comprehend – emergent complexity – emergent simplicity – emergent properties will be lost to reduction adaptation and evolution – two way interaction between the system and the environment – a decentralised process acting on local information – goal seeking adaptation, self referencing feedback and learning

7. Spring 2010 - ÇGIE 398 - lecture 47 complexity measures – the degree of complexity can be expressed in terms of structural aspects, the complexity of structure – it can also be measured in terms of function – a mathematical measure of complexity is given by the amount of information needed to describe it – the length of the binary string that can contain 2 messages is 1; for 4 or 2 2 messages, it is 2; for 8 or 2 3 messages it is 3 where log 2 (8)=3 etc. – for a complex system with k possible states we need N bits of information where N = log 2 (k) – these ideas originated in communication theory and are relevant in combinatorial mathematics also as the problem of computational complexity

8. Spring 2010 - ÇGIE 398 - lecture 48 systems thinking and complexity in ST, we can define a system as “interacting components with emergent properties” whether the system is complex or simple ST and complexity share a lot of concepts it is not clear yet if the mathematical constructs and results from complexity research can be directly applied to the study of socio-economic or socio-technical human systems however an understanding of complexity will help us understand human systems and the “soft” methods of inquiry that are needed to study them

9. Spring 2010 - ÇGIE 398 - lecture 49 readings on complexity The literature on complexity is vast and not all of it very accessible because of the mathematics involved. You must read Michel Baranger’s article: “Chaos, complexity and entropy: a physics talk for non physicists” and Richard Seel’s “Complexity and OD” under “Lecture 4” on the website. Another article written from the management point of view is Jonathan Rosenhead’s “Complexity theory and management practice”. This article is optional and is available in the “Resources” area of the course site.