@conference {1506022,
	title = {Applying Multi-Agent Techniques to Cancer Modeling },
	booktitle = {Workshop on Multiagent Sequential Decision Making in Uncertain Domains(MSDM) at AAMAS 2011	},
	year = {2011},
	abstract = {Each year, cancer is responsible for 13\% of all deaths worldwide.
In the United States, that percentage increases to 25\%, translating
to an estimated 569,490 deaths in 2010 [1]. Despite significant
advances in the fight against cancer, these statistics make clear the
need for additional research into new treatments. As such, there has
been growing interest in the use of computer simulations as a tool
to aid cancer researchers. We propose an innovative multi-agent
approach in which healthy cells and cancerous cells are modeled
as opposing teams of agents using a decentralized Markov decision
process (DEC-MDP). We then describe changes made to traditional
DEC-MDP algorithms in order to better handle the complexity and
scale of our domain. We conclude by presenting and analyzing
preliminary simulation results. This paper is intended to introduce
the cancer modeling domain to the multi-agent community with
the hope of fostering a discussion about the opportunities and challenges it presents. Given the complexity of the domain, we do not
claim our approach to be a definitive solution but rather a first step
toward the larger goal of creating realistic simulations of cancer.},
	author = {Brown, Matthew and Bowring, Emma and Shira Epstein and Mufaddal Jhaveri and Maheswaran, Rajiv and Parag Mallick and Shannon Mumenthaler and Povinelli, Michelle and Tambe, Milind}
}
