We present a hybrid agent framework to produce high-level autonomous behavior for unmanned vehicles based on formal specification. High level autonomous behavior is attractive due to minimum level of central control and support for verifiable behavior results such as safety assurance. The proposed framework use linear temporal logic (LTL) to express high level agent behavior to control search, tracking, and survival activities, which are executed at a rule-based reasoning engine. The low level search and team tracking behaviors are implemented by a policy network trained with Reinforcement Learning (RL). The behavior controller is evaluated in a simulated envrionment with single-agent and multi-agent search and tracking scenarios.
Towards high-level, verifiable autonomous behaviors with temporal specifications
2019-07-01
1186159 byte
Conference paper
Electronic Resource
English
A verifiable, autonomous satellite control system
Tema Archive | 1989
|Towards an effective and adequately verifiable PPWT
Online Contents | 2010
|Towards an effective and adequately verifiable PPWT
Elsevier | 2010
|