On Plans With Loops and Noise
This work addresses the challenge of plan correctness for robotics and other stochastic applications, but it is incremental as it builds on existing logical frameworks without introducing a new paradigm.
The paper tackles the problem of defining correctness specifications for program-like plans in stochastic environments, where sensing is noisy and actions are non-deterministic, by extending Levesque's logical framework to include degrees of belief and noise, and applies this to analyze example plans.
In an influential paper, Levesque proposed a formal specification for analysing the correctness of program-like plans, such as conditional plans, iterative plans, and knowledge-based plans. He motivated a logical characterisation within the situation calculus that included binary sensing actions. While the characterisation does not immediately yield a practical algorithm, the specification serves as a general skeleton to explore the synthesis of program-like plans for reasonable, tractable fragments. Increasingly, classical plan structures are being applied to stochastic environments such as robotics applications. This raises the question as to what the specification for correctness should look like, since Levesque's account makes the assumption that sensing is exact and actions are deterministic. Building on a situation calculus theory for reasoning about degrees of belief and noise, we revisit the execution semantics of generalised plans. The specification is then used to analyse the correctness of example plans.