Circa: The Cooperatice Intelligent Real-Time Control Architecture
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Abstract
The Cooperative Intelligent Real-time Control Architecture (CIRCA) is a novel architecture for intelligent real-time control that can guarantee to meet hard deadlines while still using unpredictable, unrestricted AI methods. CIRCA includes a real-time subsystem used to execute reactive control plans that are guaranteed to meet the domain's real-time deadlines, keeping the system safe. At the same time, CIRCA's AI subsystem performs higher-level reasoning about the domain and the system's goals and capabilities, to develop future reactive control plans. CIRCA thus aims to be intelligent about real-time: rather than requiring the system's AI methods to meet deadlines, CIRCA isolates its reasoning about which time-critical reactions to guarantee from the actual execution of the se ected reactions.
The formal basis for CIRCA's performance guarantees is a
state-based world model of agent/environment interactions. Borrowing approaches from real-time systems research, the world model provides the information required to make real-time performance guarantees, but avoids unnecessary complexity. Using the world model, the AI subsystem develops reactive control plans that restrict the world to a limited set of safe and desirable states, by guaranteeing the timely performance of actions to preempt transitions that lead out of the set of states. By executing such "safe" and "stable" plans, CIRCA's real-time subsystem is able to keep the system safe (in the world as modeled) for an indeterminate amount of time, while the parallel AI subsystem develops the next appropriate plan.
We have applied a prototype CIRCA implementation to a simulated
Puma robot arm performing multiple tasks with real-time deadlines, such as packing parts off a conveyor belt and responding to asynchronous interrupts. Our experimental results show how the system can guarantee to accomplish these tasks under a given set of domain conditions (e.g., conveyor belt speed) and resource limitations (e.g., robot arm speed). Furthermore, because CIRCA reasons explicitly about its own predictable, guaranteed behaviors, the system can recognize when its resources are insufficient for the desired behaviors (e.g., parts are arriving too quickly to be packed carefully), and can then make principled modifications to its performance (e.g., temporarily stacking parts on a table) to maintain system safety. (Also cross-referenced as UMIACS-TR-93-104)