CS4 future talk: Dr Rachel Armstrong

On Wednesday 30th January, Dr Rachel Armstrong from the the Univ126219_254x191ersity of Greenwich will give the CS4 talk “A Hitchiker’s Guide to Complexity”

Building 53 Room 4025, Highfield Campus, 4-5pm. Refreshments served after the talk.

Abstract:

“This talk offers a multi-disciplinary view of complexity from the perspective of an informed amateur – an ideas hitchhiker – curating concepts relevant to its philosophical, technological and cultural importance. These ideas are co-ordinates for a hitchhiker’s map that provokes discussion about the theory, method and application of complex systems in addressing cultural agendas and how they may work as a counter point to prevalent practices. Of particular interest is how complexity may offer alternative technological systems to machines, which shape our Modern era. Although complexity is still an emerging practice and not a ‘cure-all’ to the significant challenges that we face this century, it may offer a point of reflection on the processes that underpin human development – to identify opportunities where the interests of humanity and the environment may be one and the same – say for example, by considering the Earth to be a giant ‘natural’ supercomputer.”

CS4 future talk: Dr Tobias Galla

p1On Wednesday 16th January, Dr Tobias Galla from the University of Manchester will give the CS4 talk “Chaos and noise in game theory and evolutionary dynamics”

Building 53 Room 4025, Highfield Campus, 4-5pm. Refreshments served after the talk.

Abstract:

“In the first part of the talk I will discuss the effects of intrinsic noise on the dynamics of evolutionary systems in game theory. These are conventionally described by deterministic differential equations, an approximation valid only for infinite populations. Demographic or intrinsic noise in finite populations can have profound consequences on the dynamics and lead to new phenomena such as extinction and fixation, and to noise-driven quasi cycles. I will describe how these can be characterised in simulations and with methods from statistical physics.

 In the second part of the talk I will discuss the outcome of learning in complicated games with a large number of moves. I will show that for a large range of randomly drawn games the outcome is high-dimensional chaos, limiting the ability of players to learn to play Nash equilibria. I will discuss consequences for modelling approaches in economics and finance, especially those built around equilibrium concepts.

References:

Tobias Galla, J. Doyne Farmer, Proc. Nat. Acad. Sci, Early Edition http://intl.pnas.org/content/early/2013/01/03/1109672110.abstract

Alex J. Bladon, Tobias Galla, and Alan J. McKane, Phys. Rev. E 81, 066122 (2010)

Tobias Galla, Phys. Rev. Lett. 103, 198702 (2009)”