SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Motion control in animation, simulation and visualization
Computer Graphics Forum
NeuroAnimator: fast neural network emulation and control of physics-based models
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Computational modeling for the computer animation of legged figures
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Motion Control of Virtual Humans
IEEE Computer Graphics and Applications
Dynamically Simulated Characters in Virtual Environments
IEEE Computer Graphics and Applications
Animating Human Locomotion with Inverse Dynamics
IEEE Computer Graphics and Applications
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In this chapter, we present a novel goal-orientated approach for complex virtual character behavioural simulation. Our approach is based on the concept of an artificial brain that is a simulation of real human brain activities for simulating the virtual character's behaviour in a virtual world populated with other virtual objects and characters. The control unit in the simulation system can collect and store all the information that is obtained through the virtual character's complex experience, such as learning how to walk and jump, and analyses the information to find a better solution for a specific task. Therefore the virtual character's skill in a particular task will be developed or evolved. The core techniques also include a physics-based human model for motion modelling, which is driven by muscle forces. This approach therefore produces a more accurate simulation of the real world than conventional methods. We demonstrate this by presenting an implementation of this approach.