Philippe De Wilde
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The MacLaurin Papers
Publications
Contact:
p.de_wilde@hw.ac.uk
School of MACS
Heriot-Watt University
Edinburgh EH14 5AZ
UK
0131 451 8306
secretary: 0131 451 4152
'... in a world
that is hyper-connected, socially networked, and global, the risks and
opportunities are more extreme.' DARPA Director Regina Dugan 23.3.2010.
Question 1: What are the dynamics of interacting networks? (network noise)
Question 2: What are
equilibria in fuzzy games? (linguistic and fuzzy uncertainty)
Question 3: Members of a group make a decision, assisted by agents using neural learning and fuzzy logic. How does this process converge? (uncertainty in dynamic multi-user environments)
Neuroeconomics and
dealing with uncertainty
Professional Societies
PhD students and Postdocs
Question 1: What are the dynamics of interacting networks? (network noise)
The
world is networked, and we are all part of multiple networks. Multiple
interacting networks form a complex system, and its dynamics is usually
very different from the dynamics of a single network.
Quality-of-service, for example, may depend on decision taken by nodes
in a network beyond the control of its users. Social networks interact
as well, Twitter and Facebook messages are not independent. The brain also is composed of interacting networks of neurons, astrocytes and blood vessels. Our speed of decision making, memory formation, learning and uncertainty quantification all depend on the interaction of the networks in the brain.
Question 2: What are
equilibria
in fuzzy games? (linguistic and fuzzy uncertainty)
Natural language is imprecise in describing the world. It is this imprecision that allows us to generalize, to do deduction with incomplete information, and to reach compromises. I use fuzzy linguistic variables, implemented by membership functions, to represent the uncertainty players have about the moves of other players. Games where players do not know the exact moves of the other players I call fuzzy games. Characterizing the equilibria in these games allows us to reach easier compromises in negotiation, and make better moves under uncertainty.
Question 3:
Members
of a group make a decision, assisted by agents using neural learning
and fuzzy logic. How does this process converge? (uncertainty in
dynamic multi-user environments)
Multi-agent
systems and distributed applications have to operate in an
environment where the users are part of an evolving population. Web
search engines for example have to constantly change the way they
target users with adverts. The users sometimes change their interests
and preferences randomly, but on other occasions they will copy other
users which they see as successful. This copying of other users may be
complete or partial. New users join the community, and dissatisfied or
unsuccessful users leave the community. The user community is subject
to population dynamics. I model these population dynamics using
evolutionary game theory, and use the results in the
design of multi-agent systems and distributed applications. Multiple agents have to react with intelligence when they are part of a population. I design coordination mechanisms based on micro-economics. Such mechanisms lead to agents with higher utility, a sign of intelligence in many settings.
Professional Societies
I am active in the IEEE Systems, Man, and Cybernetics Society. I am a senior member of the IEEE, and past Associate Editor of IEEE Transactions on Systems, Man, and Cybernetics, Part B - Cybernetics.I am also a member of the IEEE Computational Intelligence Society. I was a co-organizer of FUZZ-IEEE 2007 in London. I will organize UKCI 2012 in Edinburgh.
I am a Fellow of the British Computer Society.
In 1999 I spent a sabbatical at BISC, the Berkeley Initiative on Soft Computing.
PhD students
I have successfully supervised 16 PhD students up to now. There is currently an opening for a new PhD student. Contact me if you are interested in working on any of the questions listed above.Some ex-PhD students
Dr. Festus Oderanti: dynamics of business games (now at Newcastle University)
Dr. Ibrahim Venkat: face recognition with occlusion (now at University Sains Malaysia)
Dr. Amos Storkey: neural networks (now at University of Edinburgh)
Dr. Gerard Briscoe: self-organization in business ecosystems (now at University of Cambridge)
Dr. Maria Chli: interactivity and convergence of distributed systems (now at Aston University)
Prof. Juan Wang: topology of evolving networks (now at Shenzhen University)
Dr. Victor Shen: coupling of neurons, astrocytes, and the cerebrovascular system (now at China Telecom)
Prof. Fernando Buarque: neural networks (now at Universidade de Pernambuco, Brazil)
Dr. Dai-Il Kim: adaptive signal processing (now at Nuclear Safety Evaluation, Korea)
Dr. Philip Pratt: evolving neural networks (now at Imperial College London)
Dr. Fukumi Kozato: connectionism and neural networks