  Recently, there have been a lot of researches to synthesize / edit the motion
of a single avatar in the virtual environment. However, there has not been so
much work of simulating continuous interactions of multiple avatars such as
fighting. In this paper, we propose a new method to generate a realistic
fighting scene based on motion capture data. We propose a new algorithm called
the temporal expansion approach which maps the continuous time action plan to a
discrete causality space such that turn-based evaluation methods can be used.
As a result, it is possible to use many mature algorithms available in strategy
games such as the Minimax algorithm and $\alpha-\beta$ pruning. We also propose
a method to generate and use an offense/defense table, which illustrates the
spatial-temporal relationship of attacks and dodges, to incorporate tactical
maneuvers of defense into the scene. Using our method, avatars will plan their
strategies taking into account the reaction of the opponent. Fighting scenes
with multiple avatars are generated to demonstrate the effectiveness of our
algorithm. The proposed method can also be applied to other kinds of continuous
activities that require strategy planning such as sport games.
