LTLf Synthesis on First-Order Agent Programs in Nondeterministic Environments

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Hauptverfasser: Hofmann, Till, Claßen, Jens
Format: Preprint
Veröffentlicht: 2024
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author Hofmann, Till
Claßen, Jens
author_facet Hofmann, Till
Claßen, Jens
contents We investigate the synthesis of policies for high-level agent programs expressed in Golog, a language based on situation calculus that incorporates nondeterministic programming constructs. Unlike traditional approaches for program realization that assume full agent control or rely on incremental search, we address scenarios where environmental nondeterminism significantly influences program outcomes. Our synthesis problem involves deriving a policy that successfully realizes a given Golog program while ensuring the satisfaction of a temporal specification, expressed in Linear Temporal Logic on finite traces (LTLf), across all possible environmental behaviors. By leveraging an expressive class of first-order action theories, we construct a finite game arena that encapsulates program executions and tracks the satisfaction of the temporal goal. A game-theoretic approach is employed to derive such a policy. Experimental results demonstrate this approach's feasibility in domains with unbounded objects and non-local effects. This work bridges agent programming and temporal logic synthesis, providing a framework for robust agent behavior in nondeterministic environments.
format Preprint
id arxiv_https___arxiv_org_abs_2410_00726
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle LTLf Synthesis on First-Order Agent Programs in Nondeterministic Environments
Hofmann, Till
Claßen, Jens
Artificial Intelligence
Logic in Computer Science
We investigate the synthesis of policies for high-level agent programs expressed in Golog, a language based on situation calculus that incorporates nondeterministic programming constructs. Unlike traditional approaches for program realization that assume full agent control or rely on incremental search, we address scenarios where environmental nondeterminism significantly influences program outcomes. Our synthesis problem involves deriving a policy that successfully realizes a given Golog program while ensuring the satisfaction of a temporal specification, expressed in Linear Temporal Logic on finite traces (LTLf), across all possible environmental behaviors. By leveraging an expressive class of first-order action theories, we construct a finite game arena that encapsulates program executions and tracks the satisfaction of the temporal goal. A game-theoretic approach is employed to derive such a policy. Experimental results demonstrate this approach's feasibility in domains with unbounded objects and non-local effects. This work bridges agent programming and temporal logic synthesis, providing a framework for robust agent behavior in nondeterministic environments.
title LTLf Synthesis on First-Order Agent Programs in Nondeterministic Environments
topic Artificial Intelligence
Logic in Computer Science
url https://arxiv.org/abs/2410.00726