Increasing UAV Intelligence Through Learning

Platts, Jon; Howell, S.Garry; Peeling, Emma; Thie, Claire; Lock, Zoe; Smith, P.

doi:10.2514/6.2004-6413

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…Expert system is essentially a computer program system that transplants the knowledge and experience of human experts into computer through some means of knowledge acquisition [26] . It has the ability of inference and decision as the experts.…”

Section: Expert Systemmentioning

confidence: 99%

The overview for UAV Air-Combat Decision method

Xie

Wang

et al. 2014

The 26th Chinese Control and Decision Conference (2014 CCDC)

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With the rapid development of intelligent technology, sensing technology, digital communication technology and virtual reality technology etc, the research for air-combat UAV ushered in a rare opportunity. The UAV Air-Combat Decision problem has become one of the research focuses of the military field in the world. Firstly, this paper analyzes the specific process of the UAV Air-Combat Decision and divides it into four decision-making phases. Secondly, the paper introduces the research status and the decision-making methods of the various phases, to further analyze the UAV Air-Combat Decisions. Finally, the paper analyzes in detail the difficulties and the research trends of the UAV Air-Combat Decision in the future.

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Section: Expert Systemmentioning

confidence: 99%

The overview for UAV Air-Combat Decision method

Xie

Wang

et al. 2014

The 26th Chinese Control and Decision Conference (2014 CCDC)

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“…Perhaps the closest work described in the literature is that of Platts et al in [19], in which rules are learned which relate the behaviour of an unmanned aircraft to success in a particular mission. The approach described in this paper is similar in that it involves learning rules which relate entity behaviour to unwanted hazardous consequences.…”

Section: Existing Applications Of Simulation In Safetymentioning

confidence: 99%

System of Systems Hazard Analysis Using Simulation and Machine Learning

Alexander

Kazakov

Kelly

2006

Lecture Notes in Computer Science

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Abstract. In the operation of safety-critical systems, the sequences by which failures can lead to accidents can be many and complex. This is particularly true for the emerging class of systems known as systems of systems, as they are composed of many distributed, heterogenous and autonomous components. Performing hazard analysis on such systems is challenging, in part because it is difficult to know in advance which of the many observable or measurable features of the system are important for maintaining system safety. Hence there is a need for effective techniques to find causal relationships within these systems. This paper explores the use of machine learning techniques to extract potential causal relationships from simulation models. This is illustrated with a case study of a military system of systems.

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An Effective and Scalable Approach for Swarm-on-Swarm Air Combat Decision

Zhang

Han

et al. 2022

Lecture Notes in Electrical Engineering

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Increasing UAV Intelligence Through Learning

Cited by 5 publications

References 2 publications

The overview for UAV Air-Combat Decision method

The overview for UAV Air-Combat Decision method

System of Systems Hazard Analysis Using Simulation and Machine Learning

An Effective and Scalable Approach for Swarm-on-Swarm Air Combat Decision

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