CS4 future talk: Roman Frigg

On Wednesday 27th February, Dr Roman Frigg, London School of Economics, will give the friggCS4 talk “Laplace’s Demon and the Adventures of his Apprentices”

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


“The sensitive dependence on initial condition associated with nonlinear models imposes limitations on the models’ predictive power. These limitations have been widely recognised and extensively discussed. In this paper we argue that the severity of these limitations notwithstanding, we haven’t seen the worst yet: it is structural model error rather than sensitive dependence that truly limits our ability to make useful predictions with nonlinear models. If a nonlinear model has only the slightest structural error, then its ability to generate useful prediction is lost. This puts us in a worse epistemic situation than sensitive dependence because we can guard against the effects of sensitive dependence by replacing deterministic predictions by probabilistic predictions, a route that is foreclosed in the case of structural model error. We reach this conclusion by retelling the tale of Laplace’s demon, but with a twist. In our rendering the Demon has two apprentices, the Freshman Apprentice and the Senior Apprentice, who have abilities that fall short of the Demon’s in ways that turns them into explorers of sensitive dependence and structural error respectively. We discuss in what way the problems we describe affect actual modelling projects and end by making a tentative suggestion about how to guard against the worst effects.”

CS4 future talk: Prof Scott Moss

On Wednesday 13th February, Professor Scott Moss will give the CS4 talk “Simplicity in Practice: The Failure of Social Modelling”scott-moss

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


“Mainstream economics and disciplines such as political science that have been influenced by it are bad science because they rest on theories and models that neither describe any world we can imagine ever to exist nor, unless there is no significant change or volatility,  forecast accurately anything about the worlds we inhabit.  Econometric models are just complicated means of extrapolation and other approaches such as dynamic stochastic general equilibrium models ignore central and dominating features of social processes, especially social interaction and influence.

The main justification for producing social models that describe worlds of fantasy is that the models are simple.  Sometimes, this simplicity is justified by appeal to a distortion of Occam’s Razor.  In my talk, I am going to address the issue of simplicity in modelling.  I will accept a dictum of Einstein that theories should be comprised by ” irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience.”  The key issue here is what is meant by the clause starting “without having to surrender ….”

The issue of simplicity is also important when assessing the value of applications of physical modelling approaches to social modelling coming under the heading of “complexity science”.  These typically do capture social interaction and, often enough, endogenous volatility but they are also very simple and there is no assessment of the extent to which they misrepresent any actual data of experience or fail to capture essential features of relevant social processes.

I will look at ways of incorporating the data of experience into social model designs and implementations; I will describe a process for determining which data of experience are to be captured in our models; I will suggest an approach to establishing measures of simplicity of models and I will demonstrate some prototype software for validating outputs from simulation models by linking them explicitly to specific data of experience.

If there is time, I will suggest how we might get from the specific, grounded theories we call models to more abstract models capturing more general statements of relationships and behaviour without doing violence to the data of experience “for the sake of simplicity”.

ICSS Doctoral Training Centre

The CS4 is the seminar series for the Institute for Complex Systems Simulation Doctoral Training Centre (ICSS DTC). This multi-million pound EPSRC centre is currently the home to over 70 PhD students which along with a dedicated team of academics, makes it one of the largest complexity research groups in the world. Last year the ICSS DTC held an open day. If you are interested in applying for a fully funded 4 year doctoral program at the ICSS DTC, the please view the video below and then get in touch with us at icss@soton.ac.uk.