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• W162316079 abstract "Introduction AI planning was born into a simple world: baby’s blocks, slow robots, benign and cooperative environments. Now, as a maturing technology, AI planning is facing the real world: satellites, jets, the World Wide Web, and tax law. Moving planners and plan executives out of research labs and into industrial and public applications is difficult for many reasons; my focus here is on the numerous confidence, certification, and reliability issues faced in the real world. In particular, many of the domains to which planning seems most suited (e.g., autonomous vehicles such as satellites and aircraft) are mission critical, in that system failures can lead to catastrophic results: loss of life or huge costs. Traditional aircraft and satellite control systems are extensively tested and certified to behave in very well-understood ways. Substituting an AI planning system and plan executor for a Fortran satellite control routine will take a lot of convincing. In this paper, I take the position that the best way to address these issues is through the use of an inherently self-validating planning and execution system. That is, a system in which the planner generates plans satisfying certain verifiable properties (e.g., timeliness and correctness), which are then predictably and reliably executed by the executive. In abstract form, this type of system is essentially a high-level paradigm: the system designer provides a description of primitive sensing and control actions, a description of the domain and its dynamics, and a description of the system’s goals. Then, conceptually at least, the system generates and executes a plan composed of primitives and combination functions (control logic) to reliably achieve the goals. Once the system code itself has been certified, the only further verification/certification requirements apply to the input models of primitives and the domain; each plan (program) is itself verified automatically during generation. The popularity of such classical planner/executor architectures waned during the 1980s as reactive systems dawned, but more recently the community has almost converged on multi-layer architectures incorporating planners with reactive plan execution engines. In the transition, however, many of the advantages of the classical architecture have been lost: some planners now advise rather than program, and execution engines themselves are frequently running complex, handcoded, unbounded skeletal/hierarchical plans. These systems do not provide the advantages of the automatic programming paradigm. So, let this position paper act as a call to arms: bring back predictability, execution semantics, plan verification and other such features. Stem the rampant growth of plan executor features in favor of developing accurate models of how the existing systems actually work, so that projective planners can build plans rather than simply turning on and off humanbuilt plans. With a more rigorous understanding of the performance features of complex plan execution systems like RAPs (Firby 1987), their powerful flexibility can be used in the context of verified systems for mission critical domains. It is important to note that the drive for a more predictable system does not necessarily require us to abandon the recognized advantages of new methods like reactive execution. For example, the Cooperative Intelligent Real-Time Control Architecture (CIRCA) (Musliner, Durfee, 8~ Shin 1993; 1995) roughly follows the model, with enhancements designed to handle a variety of realistic resource limitations including both planning time and execution time. CIRCA also incorporates some of the fairly recent advances in planning and execution techniques (e.g., indexical-functional variables (Agre & Chapman 1987), reactive execution). The following sections provide more detail on how CIRCA’s plan execution component uses these techniques while also providing a strictly predictable execution behavior that CII~CA relies on to enforce guaranteed plans for mission-critical domains." @default.
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• W162316079 title "Plan Execution in Mission-Critical Domains" @default.
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