} // End evaluateActionUtility
/// <summary>
/// Gets the appraisal score.
/// </summary>
/// <returns>The appraisal score.</returns>
/// <param name="factorPlant">Factor plant.</param>
private static float getAppraisalScore(FactorPlant factorPlant)
{
IFactor factor = new FactorAssembler().AssembleFactor(factorPlant);
Appraisal appraisal = factor.Evaluate(null);
return(appraisal.BasicScore);
}
/// <summary>
/// Evaluates the utility measures of the given actions by adding up the basic scores
/// calculated by all factors (per action). It then picks the action with the highest
/// score.
/// </summary>
/// <param name="actions">Actions.</param>
///
/// TODO: the blocks of code for initializing factors and getting the
/// appraisals of actions could probably be abstracted into a separate
/// method.
///
/// TODO: this could be done similarly to the Open Closed Principle
/// example in the PluralSight course aboud the SOLID principles of
/// Object Oriented Software Design by Steve Smith.
private static AIAction evaluateActionUtility(List <AIAction> actions)
{
float previousScore = 0.0f;
AIAction bestScoreAction = null;
foreach (AIAction action in actions)
{
float totalScore = 0.0f;
FactorPlant factorPlant = null;
factorPlant = new FightingStyleRankFactorPlant("Factor Plant");
IFactor fightingStyleRankFactor = new FactorAssembler().AssembleFactor(factorPlant);
// TODO: this assumes that the fighting style rank needed here
// is always the first one. In the event the character is proficient
// in more than one styles this could prove problematic.
// This is also a problem because it creates a dependency of this
// class on FightingStyleRankFactor.
((FightingStyleRankFactor)fightingStyleRankFactor).Rank = _input.OpponentRanks[0];
Appraisal appraisal = fightingStyleRankFactor.Evaluate(action);
//DebugConsole.Log ("Score for Fighting Style Rank is: " + appraisal.BasicScore);
totalScore += appraisal.BasicScore;
factorPlant = null;
factorPlant = new TechniqueProficiencyFactorPlant("Factor Plant");
IFactor techniqueProficiencyFactor = new FactorAssembler().AssembleFactor(factorPlant);
appraisal = techniqueProficiencyFactor.Evaluate(action);
//DebugConsole.Log ("Score for Technique Proficiency is: " + appraisal.BasicScore);
totalScore += appraisal.BasicScore;
factorPlant = null;
// Get the action's measure of utility in terms of the character's
// physical condition.
factorPlant = new PhysicalConditionFactorPlant("Factor Plant");
IFactor physicalConditionFactor = new FactorAssembler().AssembleFactor(factorPlant);
appraisal = physicalConditionFactor.Evaluate(action);
//DebugConsole.Log ("Score for Physical Condition is: " + appraisal.BasicScore);
totalScore += appraisal.BasicScore;
factorPlant = null;
// Get the action's measure of utility in terms of the character's
// attacker body part status.
factorPlant = new AttackerBodyPartFactorPlant("Factor Plant");
IFactor attackerBodyPartFactor = new FactorAssembler().AssembleFactor(factorPlant);
appraisal = attackerBodyPartFactor.Evaluate(action);
//DebugConsole.Log ("Score for Attacker Body Part is: " + appraisal.BasicScore);
totalScore += appraisal.BasicScore;
// Get the action's measure of utility in terms of the preceding
// actions performed by the AI Character.
factorPlant = new ActionHistoryFactorPlant("Factor Plant");
IFactor actionHistoryFactor = new FactorAssembler().AssembleFactor(factorPlant);
// TODO: this is a problem because it creates a dependency of
// this class on ActionHistoryFactor.
((ActionHistoryFactor)actionHistoryFactor).Strategy = _input.Strategy;
appraisal = actionHistoryFactor.Evaluate(action);
//DebugConsole.Log ("Score for Action History is: " + appraisal.BasicScore);
totalScore += appraisal.BasicScore;
float randomElement = Random.Range(0.0f, 1.0f);
//DebugConsole.Log ("Random element is: " + randomElement);
totalScore += randomElement;
//DebugConsole.Log ("Total score for action " + ((FightingTechniqueAction)action).Proficiency.name + " is: " + totalScore);
if (totalScore > previousScore)
{
previousScore = totalScore;
bestScoreAction = action;
}
} // End foreach
return(bestScoreAction);
} // End evaluateActionUtility