private void FullRun()
{
RobbyWorld world = new RobbyWorld(10, 10, 0.5f);
IList <Reaction> rules = world.GenerateRandomRules();
int score = world.FullRun(200, rules);
Debug.Log(world.Log);
Debug.Log($"Final score = {score}");
}
private void OneTurn()
{
(int row, int col)pos1, pos2;
Tile[] situation = new Tile[TileUtil.NUM_NEIGHBORS];
RobbyWorld world = new RobbyWorld(10, 10, 0.5f);
IList <Reaction> rules = world.GenerateRandomRules();
StringBuilder sb = new StringBuilder();
int ruleIndex;
pos1 = world.RobbyPos;
world.GetSituationAt(pos1, situation);
ruleIndex = TileUtil.ToDecimal(situation);
sb.AppendFormat(
"Robby's position: ({0},{1})\n", pos1.row, pos1.col);
sb.AppendFormat(
"Robby's situation: {0} [ {1} ]\n",
ruleIndex, TileUtil.ToString(situation));
sb.AppendFormat(
"Robby's action to take for situation {0}: {1}\n",
ruleIndex, rules[ruleIndex]);
sb.AppendFormat("Robby's original score: {0}", world.Score);
sb.AppendLine("\nActing up...");
world.NextTurn(rules);
pos2 = world.RobbyPos;
sb.AppendFormat(
"Robby's new position: ({0},{1})\n", pos2.row, pos2.col);
sb.AppendFormat(
"Situation in original position: {0}\n",
world[pos1.row, pos1.col]);
sb.AppendFormat("Robby's new score: {0}", world.Score);
Debug.Log(sb.ToString());
}
private void Optimize()
{
System.Random random = new System.Random();
RobbyWorld world = new RobbyWorld(10, 10, 0.5f);
GeneticAlgorithm <Reaction> ga = new GeneticAlgorithm <Reaction>(
200,
0.9f,
0.1f,
() => new Ind <Reaction>(world.GenerateRandomRules()),
(new TournamentSelection <Reaction>(random)).Select,
(new OnePointCrossover <Reaction>(random)).Mate,
(new FlipEnumMutation <Reaction>(0.1f)).Mutate,
(ind) => { world.Reset(); ind.Fit = world.FullRun(200, ind.GenesView); },
random);
ga.Init();
Ind <Reaction> best = ga.Run(1000, float.PositiveInfinity);
Debug.Log($"Best fitness is {best.Fit}");
}
