NANIA@CPM
(Spetember
2005 - June 2009)
Summary of NANIA in
general:
NANIA is a
collaborative project aimed at
finding efficient ways to apply computation and rigorous analysis to
complex
systems in fields such as ecology, earthquakes, epidemics and social
science. It is funded for 4 years as a network of
researchers by the EPSRC as part of its Novel Computation
Initiative. The Funded Institutions are the universities of Edinburgh; Manchester; Herriot-Watt; and Manchester Metropolitan (here).
We will
develop computer models
which represent complex systems and can be validated by comparison with
experimental data collected by our collaborators. These
models are based on “autonomes” which
represent individuals (animals, species, genes, grains of rock, people)
which
interact via networks which represent their connections (spatial
adjacency,
predator-prey relationship, gene in same phonotype, friendship or kin). The system is the subject to some
external
driving (food resource, changing environment, applied stress).
The dynamics
of these systems typically
involves evolution of both the autonomes and the networks until a
“steady
state” is reached – by which we mean that although the autonomes and
network
may continue to evolve, certain global features (number of animals,
mean connectivity,
total use of resource, temperature, plate movement) reach constant
values when
averages over time. The nature of these
steady states is unknown, as are the general condition which cause them
as
opposed to a collapse of the system.
Indeed, even defining global properties which encapsulate the
complexity
of the system without describing every detail is problematic and
ambiguous.
NANIA involves a twin track
approach. Specific researchers will make progress in building
models of specific systems: food webs, ecologies, earthquakes, gene
flow and social organisation. This work will illuminate those
areas, and find important results specific to those fields. The
second, collaborative track will involve pooling our computational
expertise to produce efficient and novel ways of solving the problems
and analysing our results in the more abstract framework of
coarse-graining the complexity to find the common principles which
govern the systems. The NANIA collaboration extends beyond
the work funded in this proposal: other work not funded here will
contribute to the second track through a series of workshops, and
we adopt an open policy of extending our modelling expertise to other
areas where autonome modelling has yet to make an impact.
Summary of NANIA at the
CPM:
Social systems are a rich source for
abstract models of coordination and control that have more general
application. Where we study conditions that facilitate the
spontaneous specialisation of skill and function, and mechanisms for
the emergence of groups. Specialisation of autonomes
(individuals) allows all aspects of an environment or problem to be
exploited in parallel with the minimum of competition – an attractive
paradigm for novel computing, particularly if it can emerge from
homogeneous underlying hardware. In ecology the driving force is
biological evolution, whilst in social systems the process can be the
result of coordination between the individuals. Specialisation
and group formation are most effective when they occur together since
they are mutually reinforcing: one species creates a niche for
the other. The formation of cooperative groups makes it easier
for members to develop specialise skills because they can rely upon
others in the group to provide for their other needs.
If benefits do not require individual
sacrifice, group formation is stable, but in other cases the
possibility of “cheats” taking the benefit without making the sacrifice
can make this unstable. Social mechanisms that stabilise groups against
“cheats” include: kin-based preference, reputation, tag-based
recognition and institutional mechanisms (e.g. contracts).
We will construct of a series of related
simulations and mathematical models at several different levels of
abstraction based on the high level SDML language.
Individual-based simulations will be constructed based on observed
social mechanisms. The exploration of these will suggest more
abstract simulations that focus on possible the key mechanisms involved
(e.g. tag-based group formation). Different "regions" of emergent
behaviour in the abstract simulations will be "mapped out", and further
mathematical approximations will be drawn up based upon inspection of
these behaviour. Once a reasonable understanding of the seperate
mechanisms has been achieved abstract mechanisms will be combined in
pairs to explore some of the "synergies" and "competition" between them.
People:
Projects, Workshops and Special Issues
arinsing out of the Project
Selected Relevant Publications
at the
CPM:
During the project
Edmonds, B. (in press)
Computational
modelling and social theory – the dangers of numerical representation.
In Mollona, E. (ed.) Computational Analysis of Firm Organisations and
Strategic Behaviour, Routledge.
Edmonds, B. (2009) The Nature of Noise. In Squazzoni, F. (Ed.)
Epistemological Aspects of Computer Simulation in the Social Sciences.
LNAI 5466:169-182. (
http://cfpm.org/cpmrep156.html).
Galán, J. M., Izquierdo, L. R., Izquierdo, S. S., Santos, J. I.,
del Olmo, R., López-Paredes, A. and Edmonds, B. (2009). Errors
and Artefacts in Agent-Based Modelling. Journal of Artificial Societies
and Social Simulation 12(1)1 (
http://jasss.soc.surrey.ac.uk/12/1/1.html).
Edmonds, B., Norling, E. and Hales, D. (2009) Towards the Emergence of
Social Structure. Computational and Mathematical Organization
Theory, 15(2):78–94. (http://cfpm.org/cpmrep173.html)
Alam, S.J., Edmonds, B. and Meyer, R. (2009)
Identifying Structural Changes in Networks
Generated from Agent-based Social Simulation Models. In
Ghose, A., Governatori, G. and Sadananda, R. (eds.) Agent Computing and
Multi-Agent Systems, 10th Pacific Rim International Conference on
Multi-Agents, PRIMA 2007,
Bangkok, Thailand, November 21-23, 2007. Revised Papers. Springer LNAI
5044:298-307. (
http://cfpm.org/cpmrep176.html)
Norling, E., Powell, C and Edmonds, B. (2008)
Cross-Disciplinary Views on Modelling
Complex Systems.
In. David, N. & Sichman, J.S. (Eds.) Multi-Agent-Based
Simulatin
IX, Springer, Lecture Notes in Artificial Intelligence, 5269:183-194.
Polhill, J. G. and Edmonds, B. (2007)
Open
Access for Social Simulation. Journal of Artificial
Societies and
Social Simulation, 10(3). (
http://jasss.soc.surrey.ac.uk/10/3/10.html).
Edmonds, B. (2007)
Artificial Science - a Simulation to Study
the Social Processes of Science. In Edmonds, B., Hernandez,
C. and Troitzsch, K. G. (eds.) (2007) Social Simulation: Technologies,
Advances and New Discoveries. IGI Publishing. (
http://cfpm.org/cpmrep138.html)
Edmonds, B. (2006)
The
Emergence
of
Symbiotic Groups Resulting From
Skill-Differentiation and Tags.
Journal
of Artificial Societies and
Social Simulation, 9(1). (
http://jasss.soc.surrey.ac.uk/9/1/10.html).
Edmonds (2006)
How are
physical
and social spaces related? - cognitive agents as the necessary
"glue". In
Billari, F. et al. (eds.) Agent-Based Computational Modelling:
Applications in demography, social, economic and environmental
sciences. Springer Verlag, 195-214. (
http://cfpm.org/cpmrep127.html)
Edmonds, B. Terán, O. and Polhill, G. (2006)
To the Outer Limits and Beyond –
characterising the envelope of sets of social simulation trajectories.
1
st World Congress on Social Simulation (WCSS'06), Kyoto,
Japan, August, 2006. (
http://cfpm.org/cpmrep162.html)
Norling, E. and Edmonds, B. (2006)
Why
it is Better to be SLAC than Smart. 1
st World
Congress on Social Simulation (WCSS'06), Kyoto,
Japan, August, 2006.
Edmonds, B. and Norling, E. (2006) Integrating Learning and Inference
in Multi-Agent Systems Using Cognitive Context. 7
th
International Workshop on Multi-Agent-Based Simulation (MABS'06),
Japan, July 2006. (
http://cfpm.org/cpmrep159.html)
Hales, D. and Edmonds, B. (2005)
Applying
a socially-inspired technique (tags) to improve cooperation in P2P
Networks, IEEE Transactions in
Systems, Man and Cybernetics, 35:385-395. (
http://cfpm.org/cpmrep134.html).
Edmonds, B. and Hales, D. (2005)
Computational Simulation
as
Theoretical Experiment, Journal of Mathematical Sociology
29(3):209-232. (
http://cfpm.org/cpmrep106.html).
Moss, S. and Edmonds, B. (2005)
Sociology and Simulation: -
Statistical and Qualitative Cross-Validation, American Journal of
Sociology, 110(4) 1095-1131. Previous version accessible as (
http://cfpm.org/cpmrep105.html).
Edmonds, B. (2005)
Simulation and
Complexity - how they can relate. In Feldmann, V. and
Mühlfeld, K. (eds.) Virtual Worlds of Precision - computer-based
simulations in the sciences and social sciences. Lit Verlag 5-32. (
http://cfpm.org/cpmrep118.html)
Edmonds, B. (2004)
Using Localised
‘Gossip’ to Structure Distributed
Learning.
CPM
Report 04-142, MMU. (
http://cfpm.org/cpmrep142.html).
Presented at the
AISB
2005 Symposium on
Socially Inspired
Computing.
Leading up to the project (i.e. those particularly relevant to it)
Edmonds, B. & Bryson, J. (2004)
The
Insufficiency of Formal Design Methods - the necessity of an
experimental approach for the understanding and control of complex MAS.
In Jennings, N. R. et al. (eds.) Proceedings of the 3
rd
Internation
Joint Conference on Autonomous Agents & Multi Agent Systems
(AAMAS'04), July 19-23, New York, ACM Press, 938-945. (
http://cfpm.org/cpmrep128.html).
Edmonds, B. (2004)
Using the
Experimental Method to Produce Reliable Self-Organised Systems.
In Brueckner, S. et al. (eds.) Engineering Self Organising Sytems:
Methodologies and Applications, Springer,
Lecture Notes in Artificial Intelligence, 3464
:84-99. (
http://cfpm.org/cpmrep131.html)
Edmonds, B. (2004)
Artificial
Science – a simulation test-bed for
studying the social processes of science.
CPM
Report 04-138, MMU. (
http://cfpm.org/cpmrep138.html).
The 2
nd International Conference of the
European Social Simulation Association (ESSA 2004), Valadollid, Spain.
16-19th September 2004.
Hales, D. and Edmonds, B. (2003)
Can
Tags Build Working Systems? - From MABS to ESOA. In Serugendo,
G. Di M., et al. (eds.) Engineering Self-Organising Systems. Springer,
Lecture Notes in Artificial Intelligence, 2977:186-194. (
http://cfpm.org/cpmrep117.html)
Hales, D. and Edmonds, B. (2003)
Evolving
Social Rationality for MAS using “Tags”, In Rosenschein, J. S.,
et al. (eds.) Proceedings of the 2
nd
International
Conference
on Autonomous Agents and Multiagent Systems, Melbourne, July 2003
(AAMAS03), ACM Press, 497-503. (
http://cfpm.org/cpmrep104.html)
Edmonds, B. (2002)
Exploring the Value of Prediction in an
Artificial Stock Market. Workshop on Adaptive Behavior in
Anticipatory Learning Systems 2002, Edinburgh, Scotland, August, 2002.
(ABiALs 2002). Butz V. M., Sigaud, O. and Gérard, P. (eds.)
Anticipatory Behavior in Adaptive Learning Systems. Springer, Lecture
Notes in Artificial Intelligence, 2684:262-281. (
http://cfpm.org/cpmrep94.html).
Edmonds, B. (2002) Learning and
Exploiting Context in Agents.
Proceedings of the 1st International Joint
Conference on
Autonomous Agents and Multiagent Systems (AAMAS), Bologna, Italy, July
2002. ACM Press, 1231-1238. (http://cfpm.org/cpmrep85.html)
Edmonds, B. (2001) Learning
Appropriate Contexts. In:
Akman, V. et. al (eds.) Modelling and Using Context - CONTEXT 2001,
Dundee, July, 2001. Lecture Notes in Artificial Intelligence,
2116:143-155. (http://cfpm.org/cpmrep78.html)