Formal Specification for Learning-Enabled Autonomous Systems

EasyChair Preprint no. 8564

Abstract

The formal specification provides a uniquely readable description of various aspects of a system, including its temporal behavior. This facilitates testing and sometimes  automatic verification of the system against the given specification. We present a logic-based formalism for specifying learning-enabled autonomous systems, which involve components based on neural networks. The formalism is based on first-order past time temporal logic that uses predicates for denoting events. We have applied the formalism successfully to two complex use cases.

Keyphrases: First-order LTL, formal specification, Learning-enabled systems, neural networks

@Booklet{EasyChair:8564,
  author = {Saddek Bensalem and Chih-Hong Cheng and Xiaowei Huang and Panagiotis Katsaros and Adam Molin and Dejan Nickovic and Doron Peled},
  title = {Formal Specification for Learning-Enabled Autonomous Systems},
  howpublished = {EasyChair Preprint no. 8564},

  year = {EasyChair, 2022}}