Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Team formation with realistic crowd simulation behaviour is a challenge in computer graphics, multi-agent control and social simulation. ,  propose a framework of crowd formation via hierarchical planning, which includes cooperative-task, coordinated-behaviour and action-control planning. In cooperative-task planning,  improve the grid potential field to achieve global path planning for a team. In coordinated-behaviour planning,  propose a time-space table to arrange behaviour scheduling for a movement. In action-control planning,  combine the gaze-movement angle model and fuzzy logic control to achieve agent action. Our method has several advantages: (1) The hierarchical architecture is guaranteed to match the human decision process from high to low intelligence. (2) The agent plans his behaviour only with the local information of his neighbour; the global intelligence of the group emerges from these local interactions. (3) The time-space table fully utilizes the three-dimensional information. Our method is verified using crowds of various densities, from sparse to dense crowds, using quantitative performance measures. The approach is independent of the simulation model and can be extended to other crowd simulation tasks.
['Xingce Wang', 'Na Liu', 'Shaolong Liu', 'Zhongke Wu', 'Mingquan Zhou', 'Jiale He', 'Peng Cheng', 'Chunyan Miao', 'Nadia Magnenat Thalmann']
I am writing a research paper on a idea Crowd formation via hierarchical planning
[{"from": "human", "value": "I am writing a research paper on a idea Crowd formation via hierarchical planning"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Team formation with realistic crowd simulation behaviour is a challenge in computer graphics, multi-agent control and social simulation. ,  propose a framework of crowd formation via hierarchical planning, which includes cooperative-task, coordinated-behaviour and action-control planning. In cooperative-task planning,  improve the grid potential field to achieve global path planning for a team. In coordinated-behaviour planning,  propose a time-space table to arrange behaviour scheduling for a movement. In action-control planning,  combine the gaze-movement angle model and fuzzy logic control to achieve agent action. Our method has several advantages: (1) The hierarchical architecture is guaranteed to match the human decision process from high to low intelligence. (2) The agent plans his behaviour only with the local information of his neighbour; the global intelligence of the group emerges from these local interactions. (3) The time-space table fully utilizes the three-dimensional information. Our method is verified using crowds of various densities, from sparse to dense crowds, using quantitative performance measures. The approach is independent of the simulation model and can be extended to other crowd simulation tasks."}]