Handbook of theoretical computer science (vol. B)
Cognitive modeling: knowledge, reasoning and planning for intelligent characters
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Dynamically altering agent behaviors using natural language instructions
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Virtual humans for validating maintenance procedures
Communications of the ACM - How the virtual inspires the real
Controlling individual agents in high-density crowd simulation
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
A decision network framework for the behavioral animation of virtual humans
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
Integrating Planning and Dialogue in a Lifestyle Agent
IVA '08 Proceedings of the 8th international conference on Intelligent Virtual Agents
Activity-driven populace: a cognitive approach to crowd simulation
IEEE Computer Graphics and Applications - Special issue on non-photorealistic rendering a virtual environment for teaching social skills
Creating three-dimensional animated human behaviors for virtual worlds
Creating three-dimensional animated human behaviors for virtual worlds
Temporal-Logic-Based Reactive Mission and Motion Planning
IEEE Transactions on Robotics
Situation understanding bot through language and environment
HRI '12 Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
Animating synthetic dyadic conversations with variations based on context and agent attributes
Computer Animation and Virtual Worlds
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In order to create a system capable of planning complex, constraints-based behaviors for an agent operating in a rich environment, two complementary frameworks were integrated. Linear Temporal Logic mission planning generates controllers that are guaranteed to satisfy complex requirements that describe reactive and possibly infinite behaviors. However, enumerating all the relevant information as a finite set of Boolean propositions becomes intractable in complex environments. The PAR (Parameterized Action Representation) framework provides an abstraction layer where information about actions and the state of the world is maintained; however, its planning capabilities are limited. The integration described in this paper combines the strengths of these two frameworks and allows for the creation of complex virtual agent behavior that is appropriate to environmental context and adheres to specified constraints.