// ok, if we are using a fixed rule for imitative learning that should only be valid when it is needed,
// the we don't really need to calculate a value for its support, we can just return 1
// ... maybe?
public double ReturnFixedSupport(ActivationCollection currentInput, Clarion.Framework.Core.Rule r)
{
if (PlayerChoice != null && r.OutputChunk == PlayerChoice)
{
return(1);
}
return(0);
}
// create simple rules to guide initial behavior
// based on item recommendations from the in-game store GUI,
// guidelines from strategy guides, etc.
// Independent Rule Learning (IRL) rules are not fixed,
// and may be refined by the agent's learning mechanisms
/* private void AddRules() {
* // set up a refinable action rule for each recommended item
* IRLRule itemRule = null;
*
* foreach (ItemId item in MyHero.RecommendedItemTable[(int)ItemRecommendations.Starting]) {
* itemRule = AgentInitializer.InitializeActionRule(MyAgent, IRLRule.Factory, PurchaseActions[(int)item], RecommendedItemPurchaseSupportDelegate);
*
* MyAgent.Commit(itemRule);
* }
* }
*/
// calculate the support for a recommended item purchase action
public double ComputeRecommendedItemPurchaseSupport(ActivationCollection currentInput, Clarion.Framework.Core.Rule r)
{
return(1);
}
