CHAOS: why one cannot have only an operating system for real-time applications
ACM SIGOPS Operating Systems Review
Algorithms for Scheduling Imprecise Computations
Computer - Special issue on real-time systems
Parallel programs for the transputer
Parallel programs for the transputer
Reducing problem-solving variance to improve predictability
Communications of the ACM
The concept of time in the specification of real-time systems
Real-time systems engineering and applications
CVGIP: Image Understanding - Special issue on purposive, qualitative, active vision
A structured view of real-time problem solving
AI Magazine
Hybrid problems need hybrid solutions?: tracking and controlling toy cars
Real-time computer vision
A robot that walks; emergent behaviors from a carefully evolved network
Neural Computation
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With increased processor speed and improved robotic and AI technology, researchers are beginning to design programs that can behave intelligently and interact in the real world. A large increase in processing power has come from parallel machines, but taking advantage of this power is challenging. In this paper we address the issues in designing planners for real-time AI and robotic applications, and provide guiding principles. These principles were designed to minimize the difference between the new real-time model and the standard off-line model. Applying these principles yields a better-structured application, easier design and implementation, and improved performance. The focus of the paper is on a design methodology for implementing effective planners in real-world applications. Using Ephor (our runtime environment), and applying the described planner principles, we demonstrate improved performance in a real-world shepherding application.