H. Fernlund, A. J. Gonzalez, R. F. DeMara, and M. Georgiopoulos, 
"Learning Tactical Human Behavior through Observation of a Human Actor,"revision 
pending to IEEE Transactions on Systems, Man and Cybernetics, revised and 
resubmitted on December 10, 2004.

Abstract:
It is widely accepted that the difficulty and expense involved in acquiring the 
knowledge behind tactical behaviors has been one limiting factor in the 
development of simulated agents representing adversaries and teammates in 
military and game simulations. Several researchers have addressed this problem 
with varying degrees of success. The problem mostly lies in the fact that 
tactical knowledge is difficult to elicit and represent through interactive 
sessions between the model developer and the subject matter expert. This paper 
describes a novel approach that employs Genetic Programming in conjunction with 
Context-based Reasoning to evolve tactical agents based upon automatic 
observation of a human performing a mission on a simulator. In this paper, we 
describe the process used to carry out the learning. A prototype was built to 
demonstrate feasibility and it is described herein. The prototype was rigorously 
and extensively tested. The evolved agents exhibited good fidelity to the 
observed human performance, as well as the capacity to generalize from