LTLf Synthesis on First-Order Agent Programs in Nondeterministic Environments

2024-10-01

AI Summary

This work addresses the robust strategy synthesis problem for high-order Golog agent programs based on the situation calculus in nondeterministic environments, ensuring satisfaction of Linear Temporal Logic over finite traces (LTLf) specifications. We propose the first framework integrating first-order action theories with LTLf synthesis: it constructs a finite game graph that uniformly models both program execution semantics and specification monitoring, enabling global robustness guarantees under partial environment controllability, infinite object domains, and non-local effects. Crucially, our approach dispenses with the standard assumption of full environmental control. By combining game-theoretic strategy solving with LTLf model checking, it automatically synthesizes deterministic execution strategies. Experimental evaluation demonstrates the method’s effectiveness and scalability in generating temporally correct strategies for complex, dynamic domains.

Technology Category

• Knowledge Representation and Reasoning: Logic Programming
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Multiagent Systems: Agreement, Argumentation & Negotiation

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs

Abstract

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.

Problem

• Synthesize policies for Golog agent programs in nondeterministic environments.
• Ensure temporal specifications (LTLf) are met across all environmental behaviors.
• Develop robust agent behavior using first-order action theories and game-theoretic methods.

Innovation

• Synthesizes policies for Golog agent programs
• Uses LTLf for temporal specification satisfaction
• Employs game-theoretic approach in nondeterministic environments