Centre for Complexity and DesignRecent Publications
Multilevel Systems and Policy
Jeffrey Johnson, Joyce Fortune, Jane Bromley
In: Mitleton-Kelly, Eve; Paraskevas, Alexandros and Day, Christopher eds. Edward Elgar Handbook of Research Methods in Complexity Science and their Applications. London: Edward Elgar, (In press, 2017).
Open Questions in Multidimensional Multilevel Network Science.
Johnson J.H. (2017) In: Shmueli E., Barzel B., Puzis R. (eds) 3rd International Winter School and Conference on Network Science. NetSci-X 2017. Springer Proceedings in Complexity. Springer, Cham
Global Systems Science and Policy.
Dum, Ralph and Johnson, Jeffrey (2017). In: Johnson, Jeffrey; Nowak, Andrzej; Ormerod, Paul; Rosewell, Bridget and Zhang, Yi-Cheng eds. Non-Equilibrium Social Science and Policy: Introduction and Essays on New and Changing Paradigms in Socio-Economic Thinking. Understanding Complex Systems. Cham, Switzerland: Springer, pp. 209–225.
Systems, Networks and Policy.
Johnson, Jeffrey; Fortune, Joyce and Bromley, Jane M. (2017). In: Johnson, Jeffrey; Nowak, Andrzej; Ormerod, Paul; Rosewell, Bridget and Zhang, Yi-Chang eds. Non-Equilibrium Social Science and Policy: Introduction and Essays on New and Changing Paradigms in Socio-Economic Thinking. Understanding Complex Systems. Cham, Switzerland: Springer, pp. 111–134.
Hypernetworks: Multidimensional relationships in multilevel systems.
Johnson, J.H. (2016). European Physical Journal Special Topics, 225(6) pp. 1037–1052.
Embracing n-ary Relations in Network Science.
Jeffrey Johnson, Jeffrey (2016).
In: Wierzbicki, Adam; Brandes, Ulrik; Schweitzer, Frank and Pedreschi, Dino eds. Advances in Network Science: 12th International Conference and School, NetSci-X 2016, Wroclaw, Poland, January 11-13, 2016, Proceedings. Lecture Notes in Computer Science (9564). Switzerland: Springer, pp. 147–160
Policy Design: a new area of design research and practice. [download]
Jeffrey Johnson and Matthew Cook
Abstract: Policy design is a new area of inquiry that takes the methods and traditions of design into the world of social, economic and environmental policy. Even though they may not know it, policy makers are designing future worlds and implementing these designs in the hope of realising their visions of the future. However, the methods of design are different to the methods generally used in the formation and execution of policy. In design requirements coevolve with the generation and evaluation of new systems. In policy some requirements may be ideologically fixed and pre-empt good overall solutions to. Assuming that policy design is indeed an important new area of design there are implications and opportunities for the design community. Since most policy makers have little formal knowledge of design, in the short term designers must engage in policy if policy-as-design is to be formulated in a designerly way. At the same time there is a need to educate policy makers in the theory and practice of design. The combination of research, applications, computer aided policy design, and design education in policy design creates great opportunities for the design community. When policy makers address their policy design task as designers, we can expect better policies with better outcomes[accepted for Complex Systems Design & Management (CSD&M), December 4-6, Paris 2013]
Second Order Swarm Intelligence
Vitorino Ramos, David M.S. Rodrigues, Jorge Louçã
Abstract: An artificial Ant Colony System (ACS) algorithm to solve general-purpose combinatorial Optimization Problems (COP) that extends previous AC models [21] by the inclusion of a negative pheromone, is here described. Several Travelling Salesman Problem (TSP) were used as benchmark. We show that by using two different sets of pheromones, a second-order co-evolved compromise between positive and negative feedbacks achieves better results than single positive feedback systems. The algorithm was tested against known NP-complete combinatorial Optimization Problems, running on symmetrical TSP’s. We show that the new algorithm compares favourably against these benchmarks, accordingly to recent biological findings by Robinson [26,27], and Gruter [28] where “No entry” signals and negative feedback allows a colony to quickly reallocate the majority of its foragers to superior food patches. This is the first time an extended ACS algorithm is implemented with these successful characteristics.
[accepted to International Conference on Hybrid Artificial Intelligence Systems (HAIS 2013), Lecture Notes in Artificial Intelligence, LNAI Springer Series]
Identifying news clusters using Q-analysis and Modularity
David M.S. Rodrigues
Abstract: With online publication and social media taking the main role in dissemination of news, and with the decline of traditional printed media, it has become necessary to devise ways to automatically extract meaningful information from the plethora of sources available and to make that information readily available to interested parties. In this paper we present a method of automated analysis of the underlying structure of online newspapers based on Q-analysis and modularity. We show how the combination of the two strategies allows for the identification of well defined news clusters that are free of noise (unrelated stories) and provide automated clustering of information on trending topics on news published online.
[accepted for oral presentation at the European Conference on Complex Systems 2013 in Barcelona, September 16-20]
Machine and socia intelligent peer-assement systems for assessing large student populations in massive open online education
Abstract: The European Étoile project aims to create high quality free open education in
complex systems science, including quality assured certification. Universities
and colleges worldwide increasingly use online platforms to offer courses open
to the public. Massive Open Online
Courses (MOOCs) give millions of
people access to education from prestigious universities. Although some courses
provide certification of attendance and completion, most do not provide any
academic or professional recognition since this would imply a rigorous and complete evaluation of the student’s achievements. Since the number of students enrolled may exceed tens of thousands, it
is impractical for a lecturer (or group of lecturers) to evaluate all students
using conventional hand marking. To be scalable,
assessment must be
automated. State-of-the-art
automated assessment includes multiple choice questions and intelligent marking
techniques (involving complex semantic analysis). However, none of these
alone can cope with very large student populations of students and guarantee
the evaluation quality required for higher education. The goal of this research is to create and evaluate a computer
mediated social interaction system for massive online learning communities.
This must be scalable
and able to assess fairly and accurately student coursework and examinations. We call this
approach “machine and socially intelligent peer assessment”. We describe our
system and illustrate its application. It combines peer assessment and reputation
systems to provide independent computerised assessment. Assignment of student
markers to scripts is based on reputation scores which emerge from their
marking behaviour. A simulation experiment shows how reputation-based social
structure evolves in our peer marking system.
A pilot experiment with ninety 16-year old high school students in
[accepted for The European Conference on e-learning ECEL’2013, SKEMA Business School, Sophia Antipolis, France, 30-31 October 2013]