NIMBioS Investigative Workshop: Optimal Control and Optimization for Individual-based and Agent-based Models
Participants: Folashade Agusto (NIMBioS); Gary An (Northwestern Univ Feinberg School of Medicine); Sharon Bewick (NIMBioS); Sudin Bhattacharya (The Hamner Institutes for Health Sciences); Abdelha El Jai (Université de Perpignan); Stephen Eubank (VBI); Paula Federico (Capitol Univ., Ohio); Eli Fenichel (Arizona State Univ.); Ben Fitzpatrick (Loyola Marymount Univ.); Weihao Ge (Univ. of Tennessee); Shana Gillette (Colorado State Univ.); Louis Gross (NIMBioS); Franziska Hinkelmann (Virginia Bioinformatics Institute); Ayaz Hyder (McGill Univ.); Abdul Jarrah (VBI); Jaewook Joo (Univ. of Tennessee); Hee-Dae Kwon (Inha Univ.); Dongjun Lee (Univ. of Tennessee); Jeehyun Lee (Yonsei Univ.); Suzanne Lenhart (Univ. of Tennessee); Zhao Lu (Cornell Univ.); Charles Macal (Argonne Natl. Lab.); Brian Mac Namee (Dublin Institute of Technology); Richard Medina (ORNL); Rachael Miller Neilan (Louisiana State Univ.); Virginia Pasour (ARO); David Murrugarra Tomairo (VBI); Michael North (Argonne Natl. Lab); Andrew Penland (Western Carolina Univ.); Alex Perkins (Univ. of California, Davis); Valeriy Perminov (BioTeckFarm); Ami Radunskaya (Pomona College); Steve Railsback (Lang, Railsback & Assoc.); Katarzyna Rejniak (Moffitt Cancer Center and Research Institute); René Salinas (Appalachian State Univ.); Suresh Sethi (Univ. of Texas at Dallas); Diglio Simoni (RTI International); Abdessamad Tridane (Arizona State Univ.); Alan Veliz-Cuba (Virginia Tech); Jie Xiong (Univ. of Tennessee); Jiongmin Yong (Univ. of Central Florida); Xiaopeng Zhao (Univ. of Tennessee)
Workshop Targets Control-Theoretic Approaches for Agent-based Models
Agent-based models (ABMs) are powerful computer-simulation modeling techniques that are used increasingly to understand a broad range of biological phenomena, such as tumor growth, the immune system, and the spread of infectious diseases through a population.
Researchers will gather Dec. 1-3 at the National Institute for Mathematical and Biological Synthesis (NIMBioS) on the University of Tennessee, Knoxville (UTK), campus to discuss ways to develop mathematical control theory methods for ABMs.
ABMs simulate the actions and interactions of autonomous individual parts, or agents, with a view to assessing the effects on the system as a whole. By simulating the simultaneous operation of multiple agents, ABMs can re-create and predict the actions of complex phenomena.
In order to study the effectiveness of possible interventions, such as vaccination and quarantine schemes, in biomedical problems, ABMs must be simulated numerous times to compare alternative intervention scenarios, which is a limitation of ABMs. Results of ABMs are not optimal solutions, but rather scenarios with various assumptions. Applying analytic methods to study how possible interventions affect system dynamics might be more useful. Thus, the goal of the workshop is to discuss the possibility of developing control-theoretic approaches for ABMs, which could be applied in studying interventions.
The ABM Workshop is organized by Filippo Castiglione from the Institute for Computing Applications, Rome; Volker Grimm from UFZ Center for Environmental Research, Leipzig; Reinhard Laubenbacher from the Virginia Bioinformatics Institute; and Suzanne Lenhart, NIMBioS Associate Director of Education and Outreach and UTK Professor of Mathematics.
NIMBioS Investigative Workshops involve 30-40 participants, of which about half are invited. Individuals with a strong interest in the topic can also apply to attend. For more information about the Agent-based Models Workshop and how to apply, visit http://www.nimbios.org.
The National Institute for Mathematical and Biological Synthesis (NIMBioS) brings together researchers from around the world to collaborate across disciplinary boundaries to investigate solutions to basic and applied problems in the life sciences. NIMBioS is sponsored by the National Science Foundation, the U.S. Department of Homeland Security, and the U.S. Department of Agriculture with additional support from The University of Tennessee, Knoxville.
For more information, contact Catherine Crawley at 865-974-9350 or ccrawley@nimbios.org
Participant Podcasts
Here's what participants are saying about their experience at the NIMBioS Optimal Control Investigative Workshop.
Ben G. Fitzpatrick, Loyola Marymount University, Clarence J. Wallen, S. J. Professor of Mathematics
Katarzyna Rejniak, Faculty Member, Integrative Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute
Volker Grimm, Senior Scientist, Helmholtz Center for Environmental Research
Topic: Optimal Control and Optimization for Individual-based and Agent-based Models
Meeting dates: December 1-3, 2009.
Organizers: Filippo Castiglione (Institute for Computing Applications, Rome); Volker Grimm (UFZ Center for Environmental Research, Leipzig); Reinhard Laubenbacher (Virginia Bioinformatics Institute); Suzanne Lenhart (University of Tennessee, Knoxville)
Objectives: Agent-based models are used increasingly to understand a broad range of biological phenomena, including, e.g., tumor growth, the immune system, and the spread of infectious diseases across social networks. In all these cases it would be very useful to have analytic methods available to study in general how possible interventions would affect system dynamics. The advantage of agent-based models is that they integrate local relationships to capture global emergent dynamics, without needing global parameters as input. The disadvantage of this type of model is that very few mathematical analysis methods are available to produce general descriptions of model response particularly in terms of spatio-temporal patterns arising from even fairly simple ABMs. In particular, the absence of a state space description of ABMs makes it very difficult to apply available control theory methods to study effective interventions. Applications of ABMs in situations with possible interventions by human actions (e.g. vaccination and quarantine schemes) have usually been limited to scenario analyses. In this case the models are simulated numerous times to compare alternative scenarios for intervention.
One possible approach to this problem is to construct state space models that approximate the agent-based model, similar to approaches proposed for discrete event simulations. This uses system identification methods developed for the state space model framework for agent-based simulations. Control-theoretic approaches for this modeling framework have been explored in a few cases. A first exploratory project in this direction resulted in a control method for in vitro competition of viruses. Such methods from approximate models may not work when there is spatial heterogeneity in the agent-based model (Federico, Gross and Lenhart, in preparation). Various techniques from optimal control and discrete optimization should be considered to investigate alternative formulations of control in relation to a state-space approximation and then compared to a similar formulation applied to the ABM.
This workshop brings together researchers working in agent-based models, optimal control and optimization to discuss the possible development of control theoretic approaches for agent-based models, beginning with the ones mentioned above. Alternative formulations of the approximation models and optimal control/optimization methods appropriate to each formulation will be considered.
Summary Report on the NIMBioS Investigative Workshop: Optimal Control and Optimization for Individual-based and Agent-based Models, December 1-3, 2009
The workshop began with an overview of some optimal control techniques. Among the other presentation topics were strategies involved in constructing IBMs, protocol for standardizing the reporting of results, epidemic IBMs with adaptive behavior, emergence behavior from ABMs, and the use of ABMs in films and games. Discussion sessions highlighted the fact that there are a variety of different types of ABMs and IBMs. Other topics of interest included algebraic-based control methods; aggregate model approaches to aid in 'optimal' control of IBMs; and high performance computing and large simulations in relation to IBMs.
NIMBioS Investigative Workshops involve 30-40 participants, focus on a broad topic or a set of related topics, attempt to summarize/synthesize the state of the art and identify future directions, and have potential for leading to one or more future
