Virtual cityscapes: recent advances in crowd modeling and traffic simulation
Frontiers of Computer Science in China
PLEdestrians: a least-effort approach to crowd simulation
Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
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In this paper, minimal energy control using artificial intelligence techniques is developed. A traditional feedforward neural network is used as the controller. Through learning, the controller can generate trajectory along a pre-defined path. The learning strategy is called Recurrent Averaging Learning.It takes the average of initial states and final states after a cycle of training and sets this value as the new initial and final states for next training cycle. By including the energy criterion in the cost function, this technique can generate minimal energy walking gait and still follow the reference trajectory.