Level-of-detail for cognitive real-time characters

We present a solution for the real-time simulation of artificial environments containing cognitive and hierarchically organized agents at constant rendering framerates. We introduce a level-of-detail concept to behavioral modeling, where agents populating the world can be both reactive and proactive. The disposable time per rendered frame for behavioral simulation is variable and determines the complexity of the presented behavior. A special scheduling algorithm distributes this time to the agents depending on their level-of-detail such that visible and nearby agents get more time than invisible or distant agents. This allows for smooth transitions between reactive and proactive behavior. The time available per agent influences the proactive behavior, which becomes more sophisticated because it can spend time anticipating future situations. Additionally, we exploit the use of hierarchies within groups of agents that allow for different levels of control. We show that our approach is well-suited for simulating environments with up to several hundred agents with reasonable response times and the behavior adapts to the current viewpoint.

[1]  Gary W. King,et al.  Hierarchical agent control: a framework for defining agent behavior , 2001, AGENTS '01.

[2]  Eloisa Vargiu,et al.  An Agent Architecture for Planning in a Dynamic Environment , 2001, AI*IA.

[3]  Mark S. Boddy,et al.  An Analysis of Time-Dependent Planning , 1988, AAAI.

[4]  Renato Pajarola.  Large scale terrain visualization using the restricted quadtree triangulation , 1998 .

[5]  Mark S. Boddy,et al.  Deliberation Scheduling for Problem Solving in Time-Constrained Environments , 1994, Artif. Intell..

[6]  Markus H. Gross,et al.  Hierarchical and Heterogenous Reactive Agents for Real‐Time Applications , 2003, Comput. Graph. Forum.

[7]  Michael Garland,et al.  Multiresolution Modeling for Fast Rendering , 1999 .

[8]  R. Aylett,et al.  Agent-based Continuous Planning , 2000 .

[9]  Noel O'Hara.  Hierarchical Impostors for the Flocking Algorithm in 3D , 2002, Comput. Graph. Forum.

[10]  Okan Arikan,et al.  Proxy Simulations for Efficient Dynamics , 2001, Eurographics.

[11]  Mark S. Boddy,et al.  Solving Time-Dependent Planning Problems , 1989, IJCAI.

[12]  Ronan Boulic,et al.  Proceedings of the Eurographics workshop on Computer animation and simulation '96 , 1996 .

[13]  Soraia Raupp Musse,et al.  A Model of Human Crowd Behavior , 1997 .

[14]  Daniel Thalmann,et al.  Hierarchical Model for Real Time Simulation of Virtual Human Crowds , 2001, IEEE Trans. Vis. Comput. Graph..

[15]  John Funge,et al.  Cognitive modeling: knowledge, reasoning and planning for intelligent characters , 1999, SIGGRAPH.

[16]  Okan Arikan,et al.  Efficient multi-agent path planning , 2001 .

[17]  David C. Brogan,et al.  Simulation level of detail for multiagent control , 2002, AAMAS '02.

[18]  Mark. Deloura,et al.  Game Programming Gems , 2000 .

[19]  Daniel Thalmann,et al.  Crowd simulation for interactive virtual environments and VRtraining systems , 2001 .

[20]  Taku Komura,et al.  Topology matching for fully automatic similarity estimation of 3D shapes , 2001, SIGGRAPH.

[21]  M. Gross,et al.  Fast multiresolution surface meshing , 1995, Proceedings Visualization '95.

[22]  Sarit Kraus,et al.  Planning and Acting Together , 1999, AI Mag..

[23]  Justine Cassell,et al.  Levels of Detail for Crowds and Groups , 2002, Comput. Graph. Forum.

[24]  Eloisa Vargiu,et al.  An Adaptive Approach for Planning in Dynamic Environments , 2001 .

[25]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[26]  Dieter Schmalstieg,et al.  Coarse View-Dependent Levels of Detail for Hierarchical and Deformable Models , 1999 .

[27]  Carol O'Sullivan,et al.  Men Behaving Appropriately: Integrating the Role Passing Technique into the ALOHA System , 2001 .

[28]  Jessica K. Hodgins,et al.  Simulation Levels of Detail for Real-time Animation , 1997, Graphics Interface.

[29]  Bruce Blumberg,et al.  A Layered Brain Architecture for Synthetic Creatures , 2001, IJCAI.

[30]  Dolores Cañamero,et al.  Modeling motivations and emotions as a basis for intelligent behavior , 1997, AGENTS '97.

[31]  Hugues Hoppe,et al.  View-dependent refinement of progressive meshes , 1997, SIGGRAPH.

[32]  Petros Faloutsos,et al.  Composable controllers for physics-based character animation , 2001, SIGGRAPH.

[33]  Armin Bruderlin,et al.  Hierarchical Agent Interface for Animation , 1997 .

[34]  Daniel Thalmann,et al.  Level of Autonomy for Virtual Human Agents , 1999, ECAL.

[35]  Damian A. Isla,et al.  Creature Smarts: The Art and Architecture of a Virtual Brain , 2001 .