research-article

Proof-Carrying Plans: a Resource Logic for AI Planning

Authors:

Ekaterina Komendantskaya,

Ronald P. A. PetrickAuthors Info & Claims

PPDP '20: Proceedings of the 22nd International Symposium on Principles and Practice of Declarative Programming

Article No.: 14, Pages 1 - 13

https://doi.org/10.1145/3414080.3414094

Published: 21 September 2020 Publication History

Abstract

Planning languages have been used successfully in AI for several decades. Recent trends in AI verification and Explainable AI have raised the question of whether AI planning techniques can be verified. In this paper, we present a novel resource logic, the Proof Carrying Plans (PCP) logic that can be used to verify plans produced by AI planners. The PCP logic takes inspiration from existing resource logics (such as Linear logic and Separation logic) as well as Hoare logic when it comes to modelling states and resource-aware plan execution. It also capitalises on the Curry-Howard approach to logics, in its treatment of plans as functions and plan pre- and post-conditions as types. This paper presents two main results. From the theoretical perspective, we show that the PCP logic is sound relative to the standard possible world semantics used in AI planning. From the practical perspective, we present a complete Agda formalisation of the PCP logic and of its soundness proof. Moreover, we showcase the Curry-Howard, or functional, value of this implementation by supplementing it with the library that parses AI plans into Agda’s proofs automatically. We provide evaluation of this library and the resulting Agda functions. Keywords: AI planning, Verification, Resource Logics, Theorem Proving, Dependent Types.

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Cited By

Hill AKomendantskaya EDaggitt MPetrick RKo HOrchard D(2021)Actions you can handle: dependent types for AI plansProceedings of the 6th ACM SIGPLAN International Workshop on Type-Driven Development10.1145/3471875.3472990(1-13)Online publication date: 18-Aug-2021
https://dl.acm.org/doi/10.1145/3471875.3472990

Proof-Carrying Plans: a Resource Logic for AI Planning
1. Theory of computation
  1. Semantics and reasoning

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cover image ACM Other conferences

PPDP '20: Proceedings of the 22nd International Symposium on Principles and Practice of Declarative Programming

September 2020

179 pages

ISBN:9781450388214

DOI:10.1145/3414080

General Chair:
Maurizio Gabbrielli
Department of Computer Science and Engineering, University of Bologna, Italy
,
Program Chairs:
Andreas Abel
Gothenburg University, Sweden
,
James Cheney
The University of Edinburgh, UK

Copyright © 2020 ACM.

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Published: 21 September 2020

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Engineering and Physical Sciences Research Council

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PPDP '20

PPDP '20: 22nd International Symposium on Principles and Practice of Declarative Programming

September 8 - 10, 2020

Bologna, Italy

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Cited By

Hill AKomendantskaya EDaggitt MPetrick RKo HOrchard D(2021)Actions you can handle: dependent types for AI plansProceedings of the 6th ACM SIGPLAN International Workshop on Type-Driven Development10.1145/3471875.3472990(1-13)Online publication date: 18-Aug-2021
https://dl.acm.org/doi/10.1145/3471875.3472990

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