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Co-evolutionary Learning for Cognitive Computer Generated Entities

  • Xander Wilcke
  • Mark Hoogendoorn
  • Jan Joris Roessingh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8482)

Abstract

In this paper, an approach is advocated to use a hybrid approach towards learning behavior for computer generated entities (CGEs) in a serious gaming setting. Hereby, an agent equipped with cognitive model is used but this agent is enhanced with Machine Learning (ML) capabilities. This facilitates the agent to exhibit human like behavior but avoid an expert having to define all parameters explicitly. More in particular, the ML approach utilizes co-evolution as a learning paradigm. An evaluation in the domain of one-versus-one air combat shows promising results.

Keywords

Situation Awareness Fitness Landscape Hill Climbing Baseline Algorithm Fighter Aircraft 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Xander Wilcke
    • 1
    • 2
  • Mark Hoogendoorn
    • 2
  • Jan Joris Roessingh
    • 1
  1. 1.Department of Training, Simulations, and Operator PerformanceNational Aerospace LaboratoryAmsterdamThe Netherlands
  2. 2.Department of Computer ScienceVU University AmsterdamAmsterdamThe Netherlands

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