Constraints-Based Complex Behavior in Rich Environments
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.