ja, maybe PRISM/Tempora :)

please have a look at: http://www.youtube.com/watch?v=WCOAxs40QDA

This is a presentation of AnyLogic CEO showing how mix of agent-based and discrete-event simulation can be applied in epidemics. While, this might not be the exact the case what you are looking for, however it might be useful for you.

We use our models to make suggestions to real world stake holders. But nobody know how successful we are as usually the funding runs out before we can focus on interacting with the real world stakeholder. After all we are a computer scientists and therefore the funding mostly focuses on the modelling mechanisms rather than the business application.

Here is an example of a model we used to inform managers about management strategies. As said before - how successful we were - I don't know ;-).

- http://jasss.soc.surrey.ac.uk/14/2/2.html

Some good examples for real world ABS are provided by:

- Bonabeau E (2002) Agent-based modeling: Methods and techniques for simulating human systems.

Proceedings of the National Academy of Science of the USA, 99(3): 7280-7287.

- Twomey and Cadman (2002) Agent-based modeling of customer behavior in the telecoms and media markets

You will find more useful papers if you have a look through the references of our JASSS papers

Besides academic papers there is also a professional simulation software based on ABM that promises to be useful for decision support:

- http://www.savannah-simulations.com/

Electricity Market Complex Adaptive System (EMCAS) designed by the RePast core team (Charles Macal et. al.) is used like this:

http://www.dis.anl.gov/projects/emcas.html

This may be a good example of what you are looking for.

Pedestrians and traffic simulation are very relevant examples. Examples of very successful commercial products are Legion (http://www.legion.com/), Vissim (http://vision-traffic.ptvgroup.com/en-uk/products/ptv-vissim/), Aimsun (http://www.aimsun.com/wp/). From my experience, there are significant experiences at the level of research projects, involving stakeholders, in urban planning (for instance), that do do not reach the maturity of a commercial product mostly because there wouldn't be a sufficient market...

These may help, although it is indeed hard to establish the extent to which they have been or are being used and, more importantly, fnding published work on how they were used, not just how they were built and validated:

Dray, A., Perez, P., Le Page, C., D’Aquino, P., & White, I. (2007). Who wants to terminate the game? The role of vested interests and metaplayers in the ATOLLGAME experience. Simulation & Gaming, 38(4), 494-511.

Gotts, N. M., Polhill, J. G., & Law, A. N. R. (2003). Agent-based simulation in the study of social dilemmas. Artificial Intelligence Review, 19(1), 3-92.

Tian, G., Ouyang, Y., Quan, Q., & Wu, J. (2011). Simulating spatiotemporal dynamics of urbanization with multi-agent systems—A case study of the Phoenix metropolitan region, USA. Ecological Modelling, 222(5), 1129-1138.

Zhang, Q., Ban, Y., Liu, J., & Hu, Y. (2011). Simulation and analysis of urban growth scenarios for the Greater Shanghai Area, China. Computers, Environment and Urban Systems, 35(2), 126-139.

There have been two large scale agent-based simulation models used to evaluate management strategy options in Western Australia. These models incorporated ecosystem dynamics and human activities such as mariculture, tourism, resource extraction (oil & gas, salt, fisheries....) and climatic changes.

Neither of these models is being used in an ongoing way, but my understanding is that they were used to inform the decision making processes subsequent to the studiies. More broadly there is a trend to "management strategy evaluation" (MSE) based management in a number of fisheries (South Africa, New Zealand and Australia) which depends on an ongoing cycle of testing management options in simulation against specific performance criteria, implementing the most successful strategies, reviewing performance, and adjusting the strategies and models as the situation changes .... ad infinitum.

I've attached some references -- the last few are the Australian studies, to which I've been a major contributor.

To me the biggest obstacle to the regular use of simulation models in this sort of context is that once the decision is made and implemented the baseline changes. We really need *much* more flexible systems, and an investment in the ongoing corporate knowledge of how to keep these systems reflecting reality: code doesn't just change itself, and large complex simulation models are like large complex animals with pointy teeth, if you don't treat them the right way they will nip you!

Oh bother, clicked the wrong button. Here is the attachment. Also a little paper that sketches out and demonstrates (to a small degree) the sort of flexibility we will probably need to make representative simulation models of complex systems (well, a *preprint* of it) can be found at https://www.researchgate.net/publication/235891661_Increasing_model_efficiency_by_dynamically_changing_model_representations

Article Increasing model efficiency by dynamically changing model re...

The GLOWA Danube project is also a real example of use of agent-based models by decision-makers.

Here are some links to the project:

http://www.glowa-danube.de/eng/home/home.php

http://www.glowa-danube.de/publikationen/allgemeine_infos/GLOWA_e_Danube.pdf

We have had two government funded projects where agent-based simulation was used by the emergency services in Australia. The first was around simulating bushfire evacuation for the town of Breamlea in collaboration with the Country Fire Authority. The second was around the use of sandbagging for urban flooding in the inner-Melbourne suburb of Elwood, in collaboration with the local council and the State Emergency Service. Some details here: https://sites.google.com/site/rmitagents/projects/nccarf

We have just also received government and industry funding for a larger three year project combining social science and planning expertise, where we will use agent-based simulation for modelling housing choices people make, in the context of sustainable urban development in Australia.

Best regards,

#1 link:The use of complex adaptive systems simulation in the air transport industry- partly funded by a quasi- governmental body (2013). Simulation as scenario-building, look-forward tool (like a lookup table of possible futures) to "go where no one has gone before" to detect emergent events that other conventional methods will never succeed, because they take a posteriori stance.

#2 link: an overview of  applied agent-based simulations in human systems- some real life cases were cited.

http://www.casmodeling.com/content/1/1/15#ack

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC128598/

I've been involed in two large agent based magament strategy evaluation project designed to trial differeent wats of managaging the interactions between humans, human industry,  and ecosystems. I'll post some links to specific documents, but in the interim, you can look at papers on my profile, and the profiles of Beth Fulton and Rich Little.

Hi there,

I know of UrbanSim used by Paul Wadell to study metropolitan coupled systems of urban mobility and housing applied in Ohio and elsewhere.

I also intend to fully develop this model for policy:

https://www.researchgate.net/publication/282975962_A_simple_agent-based_spatial_model_of_the_economy_tools_for_policy

Best,

Technical Report A simple agent-based spatial model of the economy: tools for policy