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
收藏
页码：7014 / 7019
页数：6
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