These are the reliance on domain-specific knowledge and the difficulties dealing with continuous search spaces. I propose a new approach to planning in continuous, dynamic, and unpredictable domains that addresses these two issues. This approach owes a great deal to recent investigations into the foundations of human conceptual knowledge. There is converging evidence in psychology, philosophy, linguistics, and robotics that human reasoning relies on a set of conceptual primitives. These primitives are schematic structures that are grounded in physical interaction with the world.
Critical points allow the use of standard search and planning techniques in continuous domains.
It is a domain-general simulator of agents applying forces. It supports action abstraction, a multi-level computational architecture, sensor integration, and the satisfaction of multiple concurrent goals. It is particularly well suited to controlling large numbers of agents in dynamic environments.