30 Jun 2016

Future Seminar in London: Policy Making Using Modelling in a Complex World, 18th July

"Policy Making Using Modelling in a Complex World" will be held on 18th July 2016 at the Food Standards Agency, 125 Kingsway, London  1-2pm (12.45pm prompt registration)

Presented by Professor Bruce Edmonds, Director of the Manchester Metropolitan University Business School.


Seminar Abstract:
The consequences of complexity in the real world are discussed together with some meaningful ways of understanding and managing such situations.  The implications of such complexity are that many social systems are fundamentally unpredictable by nature, especially when in the presence of structural change (transitions). This implies consequences for the way we model, but also for the way models are used in the policy process.

We discuss the problems arising from a too narrow focus on quantification in managing complex systems, in particular those of optimisation. We criticise some of the approaches that ignore these difficulties and pretend to approximately forecast using the impact of policy options using over-simple models.  However, lack of predictability does not automatically imply a lack of managerial possibilities. We will discuss how some insights and tools from "Complexity Science" can help with such management.  Managing complex systems requires a good understanding of the dynamics of the system in question - to know, before they occur, some of the real possibilities that might occur and be ready so they can be reacted to as responsively as possible. Agent based simulation will be discussed as a tool that is suitable for this task, especially in conjunction with model-informed data visualisation.

*Refreshments available, please bring your own lunch.

The event is free but you need to register at: https://www.eventbrite.co.uk/e/cecan-seminar-policy-making-using-modelling-in-a-complex-world-tickets-26323569505

#cfpm 

17 Jun 2016

Remember what a dump the UK was back in 1973 before we joined the EU

Of course this was not all to do with the EU, but the attitudes have changed a lot, from a largely failing inward-looking country to a creative outward-looking one. The migration of people to and from the EU helped in this change. We have had a flood of creative, hard working people entering the UK contributing towards our academic, business, financial, sporting, artistic and high-tech sectors. Please let us not go back - we were not great then at all.

22 Jun 2015

2 book chapters on complexity and policy modelling

@cfpm_org
Edmonds. B. & Gershenson, C. (2015). Modelling Complexity for Policy: opportunities and challenges. In Geyer, R. & Cairney, P. (eds.) Handbook on Complexity and Public Policy. Edward Elgar, pp. 205-220.


Introduction
For policy and decision-making, models can be an essential component, as models allow the description of a situation, the exploration of future scenarios, the valuation of different outcomes and the establishment of possible explanations for what is observed. The principle problem with this is the sheer complexity of what is being modelled.  A response to this is to use more expressive modelling approaches, drawn from the “sciences of complexity”— to use more complex models to try and get a hold on the complexity we face.  However, this approach has potential pitfalls as well as opportunities, and it is these that this chapter will attempt to make clear.  Thus, we hope to show that more complex modelling approaches can be useful, but also to help people avoid “fooling themselves” in the process.
      The chapter is basically in three parts: a general discussion about models and their characteristics that will inform the subsequent decision and help the reader understand their potential and difficulties, then a brief review of some of the available techniques, and ending with a review of some models used in a policy context.  It thus starts with an examination of the different kinds of model that exist, so that these kinds might be clearly distinguished and not confused.  In particular it looks at what it means for a model to be formal.  A section follows on the kinds of uses to which such models can be put. Then we look at some of the consequences of the fact that what we are modelling is complex and the kinds of compromises this forces us into, followed by some examples of models applied to policy issues.  We conclude by summarising some of the key danger and opportunities for using complex modelling for policy analysis.
http://www.e-elgar.com/shop/handbook-on-complexity-and-public-policy

Jager, W. & Edmonds, B. (2015) Policy Making and Modelling in a Complex world. In Janssen, M., Wimmer, M. and Deljoo, A. (eds.) Policy Practice anbd Digitial Science. Springer, pp. 57-74.


Abstract
In this chapter we discuss the consequences of complexity in the real world together with some meaningful ways of understanding and managing such situations.  The implications of such complexity are that many social systems are unpredictable by nature, especially when in the presence of structural change (transitions). We shortly discuss the problems arising from a too narrow focus on quantification in managing complex systems. We criticise some of the approaches that ignore these difficulties and pretend to prediction using simplistic models.  However, lack of predictability does not automatically imply a lack of managerial possibilities. We will discuss how some insights and tools from "Complexity Science" can help with such management.  To manage a complex systems requires a good understanding of the dynamics of the system in question - to know, before they occur, some of the real possibilities that might occur and be ready so they can be reacted to as responsively as possible. Agent based simulation will be discussed as a tool that is suitable for this task, and its particular strengths and weaknesses for this are discussed.
http://www.springer.com/gb/book/9783319127835

11 May 2015

Slides from talk on: "Possibilistic prediction and risk analyses"

Arguing for an approach for complexity scientists/modellers to interact with those making decisions (policy, business etc) in situations, in a way that does not deprive those decision makers of responsibility and which leaves them in control, whilst informing them.

A talk given at the EA Conference, Bonn, May 2015.

Abstract:
It is in the nature of complex systems that predictions that give a probability are not possible.

Indeed I argue that giving "the most likely" or "rough" prediction is more harmful than useful.

Rather an approach which maps out some of the possible outcomes is outlined. 

Agent-based modelling is ideal for producing these - including, crucially, possibilities that could not have been conceived just by thinking about it (due to the fact that events can combine in ways that are more complex than the human brain can cope with directly).

A characterisation of the real future possibilities and their nature allows some positive responses to events:
* putting in place 'early warning indicators' for the emergence of identified possibilities
* contingency planning for when they are indicated. 

Such an approach would allow policy makers to better 'drive' their decision making, without abnegating responsibility to experts
 Slides availabe at: http://www.slideshare.net/BruceEdmonds/be-eatalkfinal

12 Nov 2014

An article including quotes from me about the Turing test and the nature of intelligence in E&T

The Turing Test: brain-inspired computing's multiple-path approach
10th November 2014 By Edd Gent

About projects like the Human Brain project and the Turing Test for (so called) general intelligence.   In the Engineering and Techology magazine

Access it at: http://eandt.theiet.org/magazine/2014/11/imitation-brains.cfm
Relates to the paper:
Edmonds, B. and Gershenson, C (2012) Learning, Social Intelligence and the Turing Test – why an “out-of-the-box” Turing Machine will not pass the Turing Test. Lecture Notes in Computer Science, 7318, 182-192. http://link.springer.com/chapter/10.1007/978-3-642-30870-3_18 (previous version freely available at http://arxiv.org/abs/1203.3376)

9 Sep 2014

Paper and Slides: "Analysing a Complex Agent-Based Model Using Data-Mining Techniques"


Analysing a Complex Agent-Based Model Using Data-Mining Techniques 
By Claire Little, Bruce Edmonds, Laurence Lessard-Phillips, and Ed Fieldhouse

Presented at Social Simulation 2014, Barcelona, September.


A complex “Data Integration Model” of voter behaviour is described. However it is very complex and hard to analyse. For such a model “thin” samples of the outcomes using classic parameter sweeps are inadequate. In order to get a more holistic picture of its behaviour data- mining techniques are applied to the data generated by many runs of the model, each with randomised parameter values.
Paper at: http://cfpm.org/aacabm/analysing a complex model-v3.4.pdf
Slides at:  http://www.slideshare.net/BruceEdmonds/analysing-a-complex-agentbased-model-using-datamining-techniques

8 Sep 2014

Slides of my talk at the 2014 ESSA summer school: "Winter is coming! - how to survive the coming critical storm and demonstrate that social simulations work"

 A talk at the 2014 European Social Simulation Association summer school, at UAB in Barcelona 8th sept 2014

The talk covers some of the symptoms of hype in social simulation and argues that it needs to be more careful and rigourous. In particular that the (current) purpose of a simulation needs to be distinguished between theoretical, explanatory or predictive. Each having their own critieria.

http://www.slideshare.net/BruceEdmonds/winter-is-coming-38816017

3 Jul 2014

Edited Book: "The Complexity of Social Norms"

The Complexity of Social Norms

Editors: Maria Xenitidou, and Bruce Edmonds 

Other Authors: Elinor Ostrom, Wesley Perkins, Cristina Bicchieri, Rosaria Conte,  Marco Janssen,  Flaminio Squazzoni Christine Horne, Brigitte Burgemeestre, Hugo Mercier, Chris Goldspink, Corinna Elsenbroich, Joris Hulstijn, Yao-Hua Tan, Giulia Andrighetto, and Daniel Villatoro

ISBN: 978-3-319-05307-3 (Print) 978-3-319-05308-0 (Online)
  • Takes a fresh, fundamentally dynamic and complexity inspired approach to the study of social norms
  • Presents a new methodological and theoretical perspective to study normative behavior
  • Contributing authors provide a unique and varied perspective from departments such as philosophy, economics and political science
This book explores the view that normative behaviour is part of a complex of social mechanisms, processes and narratives that are constantly shifting. From this perspective, norms are not a kind of self-contained social object or fact, but rather an interplay of many things that we label as norms when we ‘take a snapshot’ of them at a particular instant. Further, this book pursues the hypothesis that considering the dynamic aspects of these phenomena sheds new light on them.

The sort of issues that this perspective opens to exploration include:

  • Of what is this complex we call a "social norm" composed of?
  • How do new social norms emerge and what kind of circumstances might facilitate such an appearance?
  • How context-specific are the norms and patterns of normative behaviour that arise?
  • How do the cognitive and the social aspects of norms interact over time?
  • How do expectations, beliefs and individual rationality interact with social norm complexes to effect behaviour?
  • How does our social embeddedness relate to social constraint upon behaviour?
  • How might the socio-cognitive complexes that we call norms be usefully researched?
 http://www.springer.com/social+sciences/book/978-3-319-05307-3

Table of contents (11 chapters)

  1. Front Matter

    Pages i-vi
  2. No Access
    Book Chapter
    Pages 1-8
  3. The Complex Roots of Social Norms

    1. Front Matter

      Pages 9-9
    2. Book Chapter
      Pages 11-36
    3. Book Chapter
      Pages 37-54
    4. Book Chapter
      Pages 55-79
    5. Book Chapter
      Pages 81-103
    6. Book Chapter
      Pages 105-120
  4. Methods and Epistemological Implications of Social Norm Complexity

    1. Front Matter

      Pages 121-121
    2. Book Chapter
      Pages 123-139
    3. Book Chapter
      Pages 141-160
    4. Book Chapter
      Pages 161-173
  5. Evaluating Complex Approaches to Norms

    1. Front Matter

      Pages 175-175
    2. Book Chapter
      Pages 177-188
    3. Book Chapter
      Pages 189-197
  6. Back Matter

    Pages 199-205