Persistent URL of this record https://hdl.handle.net/1887/84692
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Calculated Moves: Generating Air Combat Behaviour
The domain of air combat is complex, and machine learning methods that operate within this domain must be suited to the challenges posed by the domain. Our research shows that the dynamic scripting algorithm greatly facilitates the automatic generation of air combat behaviour models, while being sufficiently flexible to be moulded into answers to the challenges. However, ensuring the validity of the newly generated behaviour models remains to be a point of...Show moreBy training with virtual opponents known as computer generated forces (CGFs), trainee fighter pilots can build the experience necessary for air combat operations, at a fraction of the cost of training with real aircraft. In practice however, the variety of CGFs is not as wide as it can be. This is largely due to a lack of behaviour models for the CGFs. In this thesis we investigate to what extent behaviour models for the CGFs in air combat training simulations can be automatically generated, by the use of machine learning.
The domain of air combat is complex, and machine learning methods that operate within this domain must be suited to the challenges posed by the domain. Our research shows that the dynamic scripting algorithm greatly facilitates the automatic generation of air combat behaviour models, while being sufficiently flexible to be moulded into answers to the challenges. However, ensuring the validity of the newly generated behaviour models remains to be a point of attention for future research.Show less
- All authors
- Toubman, A.
- Supervisor
- Herik, H.J. van den; Spronck, P.H.M.
- Co-supervisor
- Roessingh, J.J.M.
- Committee
- Reisen, M.E.H. van; Manegold, S.; Lin, H.X.; Scholtes, J.C.; Croon, G.C.H.E. de
- Qualification
- Doctor (dr.)
- Awarding Institution
- Leiden Institute of Advanced Computer Science, Faculty of Science, Leiden University
- Date
- 2020-02-05
- Title of host publication
- SIKS Dissertation Series
- ISBN (print)
- 9789464020007
Publication Series
- Name
- 2020-01