Looking for patterns: An approach for tackling tough problems

Community member post by Scott D. Peckham

Scott D. Peckham (biography)

What does the word ‘pattern’ mean to you? And how do you use patterns in addressing complex problems?

Patterns are repetitions. These can be in space, such as patterns in textiles and wallpaper, which include houndstooth, herringbone, paisley, plaid, argyle, checkered, striped and polka-dotted.

The pattern concept can also be applied to repetitions in time, as occur in music. Those who know the temporal patterns can classify a piece of music as a blues, waltz or salsa. For each of these types of music, there are also classic dance steps, that usually go by the same name; these are patterns of movement in space and time.

These examples get to the idea that patterns can be viewed more generally as any type of repetitive structure or recurring theme that we can look for and potentially recognize or discover and then assign a memorable name to, such as “houndstooth” or “waltz”. Recognizing the pattern may then indicate a particular course of action, such as “perform dance moves that go with a waltz”.

The ability to recognize a pattern and then take appropriate action is something that we associate with intelligence. Continue reading

Methods for integration in transdisciplinary research

Community member post by Matthias Bergmann

matthias-bergmann
Matthias Bergmann (biography)

To make progress in contributing to the solution of complex real-world problems, transdisciplinary research has come to the forefront. By integrating multiple disciplines as well as the expertise of partners from societal practice, transdisciplinary researchers are able to look at a problem from many angles, with the goal of making both societal and scientific advances.

But how can these different types of expertise be integrated into both a better understanding of the problem and more effective ways of addressing it?

Colleagues and I have collected 43 methods from a number of transdisciplinary research projects dealing with a variety of research topics. We have grouped them into seven classes following an epistemological hierarchy. We start with methods in the narrower sense, progressing to integration instruments. Continue reading

Learning to tackle wicked problems through games / Aprendiendo a hacer frente a problemas perversos a través de los juegos/ Apprendre à affronter les problèmes sournois à travers les jeux

Community member post by Claude Garcia, Anne Dray and Patrick Waeber

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Claude Garcia (biography)

A Spanish version and a French version of this post are available

Can we help the next generation of policy makers, business leaders and citizens to become creative, critical and independent thinkers? Can we make them aware of the nature of the problems they will be confronted with? Can we strengthen their capacity to foster and lead stakeholder processes to address these problems?

Yes. Continue reading

Knowledge mapping technologies

Community member post by Jack Park

jack-park
Jack Park (biography)

How can you improve your thinking – alone or in a group? How can mapping ideas help you understand the relationships among them? How can mapping a conversation create a new reality for those involved?

In what follows, I draw on the work of Daniel Kahneman’s (2011) best-selling book Thinking, Fast and Slow, which explains how human thinking occurs at different speeds, from the very fast thinking associated with face-to-face conversation to the very slow thinking associated with assembling information resources into encyclopedias. I use those ideas in my descriptions of knowledge maps.

Three kinds of knowledge maps Continue reading

The path perspective on modelling projects

Community member post by Tuomas J. Lahtinen, Joseph H. A. Guillaume, Raimo P. Hämäläinen

tuomas-lahtinen
Tuomas J. Lahtinen (biography)

How can we identify and evaluate decision forks in a modelling project; those points where a different decision might lead to a better model?

Although modellers often follow so called best practices, it is not uncommon that a project goes astray. Sometimes we become so embedded in the work that we do not take time to stop and think through options when decision points are reached.

Joseph H. A. Guillaume (biography)

One way of clarifying thinking about this phenomenon is to think of the path followed. The path is the sequence of steps actually taken in developing a model or in a problem solving case. A modelling process can typically be carried out in different ways, which generate different paths that can lead to different outcomes. That is, there can be path dependence in modelling.

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Raimo P. Hämäläinen (biography)

Recently, we have come to understand the importance of human behaviour in modelling and the fact that modellers are subject to biases. Behavioural phenomena naturally affect the problem solving path. For example, the problem solving team can become anchored to one approach and only look for refinements in the model that was initially chosen. Due to confirmation bias, modelers may selectively gather and use evidence in a way that supports their initial beliefs and assumptions. The availability heuristic is at play when modellers focus on phenomena that are easily imaginable or recalled. Moreover particularly in high interest cases strategic behaviour of the project team members can impact the path of the process. Continue reading

Complexity and agent-based modelling

Community member post by Richard Taylor and John Forrester

richard-taylor
Richard Taylor (biography)

Policy problems are complex and – while sometimes simple solutions can work – complexity tools and complexity thinking have a major part to play in planning effective policy responses. What is ‘complexity’ and what does ‘complexity science’ do? How can agent-based modelling help address the complexity of environment and development policy issues?

Complexity

At the most obvious level, one can take complexity to mean all systems that are not simple, by which we mean that they can be influenced but not controlled. Complexity can be examined through complexity science and complex system models. Continue reading