Towards Formal Verification of Neuro-symbolic Multi-agent Systems

被引：0

作者：

Kouvaros, Panagiotis ^{[1
]}

机构：

[1] Imperial Coll London, London, England

来源：

PROCEEDINGS OF THE THIRTY-SECOND INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, IJCAI 2023 | 2023年

基金：

英国工程与自然科学研究理事会;

关键词：

PARAMETERIZED VERIFICATION; MODEL CHECKING;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper outlines some of the key methods we developed towards the formal verification of multi-agent systems, covering both symbolic and connectionist systems. It discusses logic-based methods for the verification of unbounded multi-agent systems (i.e., multi-agent systems composed of an arbitrary number of homogeneous agents), optimisation approaches for establishing the robustness of neural network models, and mixed-integer linear programming methods for analysing properties of neuro-symbolic multi-agent systems.

引用

页码：7014 / 7019

页数：6

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