A Leader-follower Partially Observed,
Multiobjective Markov Game
Ms. Yanling Chang, Prospective Faculty
Industrial Engineering Department
Friday, February 27, 2015 – 10:00 am
IE103
Abstract:
The leader-follower partially observed, multi-objective Markov game (LF-POMG) models a
sequential decision making situation with two intelligent and adaptive decision makers, a leader and a
follower, each of which can choose actions that affect the dynamics of the system and where these
actions are selected on the basis of current and past but possibly inaccurate state observations. The
decision makers can be cooperative, non-cooperative, or a mixture of both. The leader can consider
multiple objectives and the follower considers a single objective in selecting their decision-making
policies. The LF-POMG is a new, relatively unexamined combination of a stochastic game and a
partially observe Markov decision process (POMDP). We investigate structural properties for this
decision-making model and develop a computational procedure for finding good suboptimal solutions.
We also show how the leader’s observation quality of the follower’s state affects the performance of
the leader, representing an analysis of the value of information for the LF-POMG. We present the
results of a case study where the LF-POMG has been used to provide decision support to the manager
of a food processing facility whose objectives are to maximize facility productivity while minimizing
the risk of an intentional insertion of a biological or chemical toxin into the facility.
BIOGRAPHY:
Yanling Chang, Ph.D. Candidate, H. Milton Stewart School of Industrial & Systems Engineering, Georgia
Institute of Technology.
February 27, 2015
10:00 am