Evolving Agents for the Hanabi 2018 CIG Competition
  Hanabi is a cooperative card game with hidden information that has won
important awards in the industry and received some recent academic attention. A
two-track competition of agents for the game will take place in the 2018 CIG
conference. In this paper, we develop a genetic algorithm that builds
rule-based agents by determining the best sequence of rules from a fixed rule
set to use as strategy. In three separate experiments, we remove human
assumptions regarding the ordering of rules, add new, more expressive rules to
the rule set and independently evolve agents specialized at specific game
sizes. As result, we achieve scores superior to previously published research
for the mirror and mixed evaluation of agents.
