Hengchin Yeh, Sean Curtis, Sachin Patil, Jur van den Berg, Dinesh Manocha, Ming Lin University of...
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Transcript of Hengchin Yeh, Sean Curtis, Sachin Patil, Jur van den Berg, Dinesh Manocha, Ming Lin University of...
Hengchin Yeh, Sean Curtis, Sachin Patil, Jur van den Berg,
Dinesh Manocha, Ming LinUniversity of North Carolina at Chapel Hill
ACM 2008
Walter Kerrebijn045837621-06-2011
Introduction
Increase of agent-based methods to model virtual crowds:
• off-line (movies)• real-time (games, virtual environments)
Introduction
Agent-based approach pros:• independent decisions• different simulation parameters
Agent-based approach contras:• emergent realism from behavioral rules hard to ensure• computationally expensive• distinction between global and local path-planning
Introduction
Proposal:• Use composite agents to model different emergent behaviors:
- embody intangible factors (social, psychological)- use pre-existing collision avoidance
Related Work
• Rule-based systems• Social Forces models• Continuum Crowd theoryClaim: All these can be combined with Composite Agents approach
Composite Agents
General multi-agent system (SIMULATOR):• environment ΦEnv
• set of Agents = {A1,A2,…,An}• with states φi
• external state εi• position pi• velocity vi• geometric representation Gi
• internal state ιi• goal position, memory, mental state
Definitions
Composite Agents
General multi-agent system (SIMULATOR):• Algorithm for each agent:
• GatherNeighbors()• field of view, nearest-k neighbors• ENbr = {εk | Ak є GatherNeighbors(Ai)}
• Update()• φi ← Update(φi,ENbr,ΦEnv)
Definitions
Composite AgentsDefinitions
Composite Agent:• Basic Agent
• standard agent Ai from SIMULATOR• contains a set of Proxy Agents Pi,j
• Proxy Agent• “hands extended from the basic agent […], encouraging [other agents] to step away to avoid collision”
Composite AgentsDefinitions
Proxy Agent Pi,j• εi,j• ιi,j• acces to ιi
Composite AgentsDefinitions
Composite AgentsTypes
Different kinds of intangible factors:• Aggression• Social Priority• Authority• Protection and Guidance
Composite AgentsTypes
Aggression:• Urgency
• modeled as property Urgency• Expression of that urgency
• modeled by adding aggression proxy Pi,1
Composite AgentsTypes
Urgency:• constant
• dynamic (velocity-based, distance-based)
Composite AgentsTypes
Example Urgency
Composite AgentsTypes
Social Priority:• Priority
• modeled as property Priority• Expression of that priority
• modeled by adding priority proxy Pi,1
Composite AgentsTypes
Example Social Priority
Composite AgentsTypes
Authority:• Trailblazer
• modeled as property Trail Identifier• Expression of that trailblazer
• modeled by adding trail proxies Pi,1,Pi,2,…,Pi,m
Composite AgentsTypes
Example Authority
Composite AgentsTypes
Protection and Guidance:• Mother M and Child K
• M maintains information about K• M provides protection and guidance for K
• Expression of M’s behavior• modeled by adding a protection or guidance proxie Pi,1
Composite AgentsTypes
Protection:
Guidance:
Composite AgentsTypes
Example Protection and Guidance
Implementation
Implementation
Implementation
Proxy Updates• information contained in proxy
Dynamic StatesConditional Neighbors
• proxies not in neighbor set of parent agent, trail proxies not in neighbor sets of group members
Visualization• 2D and 3D
Experiment
Office Evacuation, Subway Station, Embassy
[Movie]
Results
Results
Results
Conclusion
• Composite agents can be succesfully used to model emergent crowd behaviors• This yields little computational overhead
Assessment
• (Almost) good paper length, but lacking information almost everywhere
• Experiments barely compare between methods or even sufficiently in the same method
• Ending seems too short, incomplete, or superficial
• Conclusion is not epic, and maybe too bold
Assessment
• The ‘math’ section seems misplaced and arbitrary, also too compact to really check its use and correctness
• Almost nothing is mentioned about goal selection, map creation, or the selection of locations of proxy agents
• Accompanying website (http://gamma.cs.unc.edu/CompAgent/) has very little information
Assessment
• The notion of ‘groups’ is not really explored
• ‘Any geometrical shape’ is not explained
• ‘Future work’ should be current work