| dc.description.abstract | The report describes the results achieved in the FFI-project 722 on synthetic decision making. It is observed how
formalised combat simulations fit the game-theoretic framework of two-player zero-sum games. The games of
Campaign, Operation Lucid and Operation Opaque are described. These games have been used for experiments with
human decision making and artificial intelligence (AI). The human experiments indicate that the game-theoretic concept
of randomisation in games of imperfect information fails to explain human decision making. Several AI techniques
were utilised in the development of automatic agents playing our three games, including rule-based systems, fuzzy
logic, genetic programming, neural nets and constraint satisfaction programming. The most significant contribution
from the project was the development of reinforcement learning (including co-evolution) algorithms for games of
imperfect information. | en_GB |