@article{2546,
  keywords = {automated learning, Computer generated forces},
  author = {Mikel Petty},
  title = {Benefits and Consequences of Automated Learning  in Computer Generated Forces Systems},
  abstract = {<p>Computer generated forces (CGF) are automated or semi-automated entities in a battlefield simulation that are generated and controlled by a computer system (the CGF system), perhaps assisted by a human operator. The idea that CGF systems can and should include automated learning capabilities has been widely asserted and accepted. However, it seems to be not so obvious that learning by CGF systems would necessarily be beneficial. For each of the three broad classes of CGF applications there are categories of learning-modified behavior for CGF systems that apparently could reduce or negate the utility of the CGF system for the application. Real and notional examples are available. The specific applications where learning by CGF systems might be useful are a subset of CGF applications.</p>},
  year = {2003},
  journal = {Information & Security: An International Journal},
  volume = {12},
  chapter = {063},
  pages = {63-74},
  month = {2003},
  doi = {http://dx.doi.org/10.11610/isij.1203},
  language = {eng},
}