TY - GEN
T1 - Effect of local population uncertainty on cooperation in bacteria
AU - Noel, Adam
AU - Fang, Yuting
AU - Yang, Nan
AU - Makrakis, Dimitrios
AU - Eckford, Andrew W.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Bacteria populations rely on mechanisms such as quorum sensing to coordinate complex tasks that cannot be achieved by a single bacterium. Quorum sensing is used to measure the local bacteria population density, and it controls cooperation by ensuring that a bacterium only commits the resources for cooperation when it expects its neighbors to reciprocate. This paper proposes a simple model for sharing a resource in a bacterial environment, where knowledge of the population influences each bacterium's behavior. Game theory is used to model the behavioral dynamics, where the net payoff (i.e., utility) for each bacterium is a function of its current behavior and that of the other bacteria. The game is first evaluated with perfect knowledge of the population. Then, the unreliability of diffusion introduces uncertainty in the local population estimate and changes the perceived payoffs. The results demonstrate the sensitivity to the system parameters and how population uncertainty can overcome a lack of explicit coordination.
AB - Bacteria populations rely on mechanisms such as quorum sensing to coordinate complex tasks that cannot be achieved by a single bacterium. Quorum sensing is used to measure the local bacteria population density, and it controls cooperation by ensuring that a bacterium only commits the resources for cooperation when it expects its neighbors to reciprocate. This paper proposes a simple model for sharing a resource in a bacterial environment, where knowledge of the population influences each bacterium's behavior. Game theory is used to model the behavioral dynamics, where the net payoff (i.e., utility) for each bacterium is a function of its current behavior and that of the other bacteria. The game is first evaluated with perfect knowledge of the population. Then, the unreliability of diffusion introduces uncertainty in the local population estimate and changes the perceived payoffs. The results demonstrate the sensitivity to the system parameters and how population uncertainty can overcome a lack of explicit coordination.
UR - http://www.scopus.com/inward/record.url?scp=85046343256&partnerID=8YFLogxK
U2 - 10.1109/ITW.2017.8278046
DO - 10.1109/ITW.2017.8278046
M3 - Conference contribution
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 334
EP - 338
BT - 2017 IEEE Information Theory Workshop, ITW 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Information Theory Workshop, ITW 2017
Y2 - 6 November 2017 through 10 November 2017
ER -