AIApr 26, 2022

On the Verification of Belief Programs

arXiv:2204.12562v31 citationsh-index: 37
Originality Incremental advance
AI Analysis

This work addresses verification challenges for belief programs, which are incremental in extending prior frameworks for high-level robot control under uncertainty.

The paper tackles the problem of verifying belief programs, a probabilistic extension of GOLOG programs for robot control under uncertainty, by proposing a formalism based on modal logic to specify properties and investigating the decidability and undecidability of verification.

In a recent paper, Belle and Levesque proposed a framework for a type of program called belief programs, a probabilistic extension of GOLOG programs where every action and sensing result could be noisy and every test condition refers to the agent's subjective beliefs. Inherited from GOLOG programs, the action-centered feature makes belief programs fairly suitable for high-level robot control under uncertainty. An important step before deploying such a program is to verify whether it satisfies properties as desired. At least two problems exist in doing verification: how to formally specify properties of a program and what is the complexity of verification. In this paper, we propose a formalism for belief programs based on a modal logic of actions and beliefs. Among other things, this allows us to express PCTL-like temporal properties smoothly. Besides, we investigate the decidability and undecidability for the verification problem of belief programs.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes