/// <summary>
/// Assigns new decision option to mental model of current agent. If empty rooms ended, old decision options will be removed.
/// </summary>
/// <param name="newDecisionOption"></param>
public void AssignNewDecisionOption(DecisionOption newDecisionOption)
{
DecisionOptionLayer layer = newDecisionOption.Layer;
DecisionOption[] layerDecisionOptions = AssignedDecisionOptions.GroupBy(r => r.Layer).Where(g => g.Key == layer).SelectMany(g => g).ToArray();
if (layerDecisionOptions.Length < layer.LayerConfiguration.MaxNumberOfDecisionOptions)
{
AssignedDecisionOptions.Add(newDecisionOption);
AnticipationInfluence.Add(newDecisionOption, new Dictionary <Goal, double>());
DecisionOptionActivationFreshness[newDecisionOption] = 0;
}
else
{
DecisionOption decisionOptionForRemoving = DecisionOptionActivationFreshness.Where(kvp => kvp.Key.Layer == layer).GroupBy(kvp => kvp.Value).OrderByDescending(g => g.Key)
.Take(1).SelectMany(g => g.Select(kvp => kvp.Key)).RandomizeOne();
AssignedDecisionOptions.Remove(decisionOptionForRemoving);
AnticipationInfluence.Remove(decisionOptionForRemoving);
DecisionOptionActivationFreshness.Remove(decisionOptionForRemoving);
AssignNewDecisionOption(newDecisionOption);
}
}
/// <summary>
/// Assigns new rule to mental model (rule list) of current agent. If empty rooms ended, old rules will be removed.
/// </summary>
/// <param name="newRule"></param>
public void AssignNewRule(Rule newRule)
{
RuleLayer layer = newRule.Layer;
Rule[] layerRules = AssignedRules.GroupBy(r => r.Layer).Where(g => g.Key == layer).SelectMany(g => g).ToArray();
if (layerRules.Length < layer.LayerConfiguration.MaxNumberOfRules)
{
AssignedRules.Add(newRule);
AnticipationInfluence.Add(newRule, new Dictionary <Goal, double>());
RuleActivationFreshness[newRule] = 0;
}
else
{
Rule ruleForRemoving = RuleActivationFreshness.Where(kvp => kvp.Key.Layer == layer && kvp.Key.IsAction).GroupBy(kvp => kvp.Value).OrderByDescending(g => g.Key)
.Take(1).SelectMany(g => g.Select(kvp => kvp.Key)).RandomizeOne();
AssignedRules.Remove(ruleForRemoving);
AnticipationInfluence.Remove(ruleForRemoving);
RuleActivationFreshness.Remove(ruleForRemoving);
AssignNewRule(newRule);
}
}
/// <summary>
/// Creates copy of current agent, after cloning need to set Id, connected agents don't copied
/// </summary>
/// <returns></returns>
public virtual Agent Clone()
{
Agent agent = CreateInstance();
agent.Archetype = Archetype;
agent.privateVariables = new Dictionary <string, dynamic>(privateVariables);
agent.AssignedGoals = new List <Goal>(AssignedGoals);
agent.AssignedDecisionOptions = new List <DecisionOption>(AssignedDecisionOptions);
//copy ai
AnticipationInfluence.ForEach(kvp =>
{
agent.AnticipationInfluence.Add(kvp.Key, new Dictionary <Goal, double>(kvp.Value));
});
agent.DecisionOptionActivationFreshness = new Dictionary <DecisionOption, int>(DecisionOptionActivationFreshness);
return(agent);
}
/// <summary>
/// Creates copy of current agent, after cloning need to set Id, connected agents don't copied
/// </summary>
/// <returns></returns>
public Agent Clone()
{
Agent agent = new Agent();
agent.Prototype = Prototype;
agent.privateVariables = new Dictionary <string, dynamic>(privateVariables);
agent.AssignedGoals = new List <Goal>(AssignedGoals);
agent.AssignedRules = new List <Rule>(AssignedRules);
//copy ai
AnticipationInfluence.ForEach(kvp =>
{
agent.AnticipationInfluence.Add(kvp.Key, new Dictionary <Goal, double>(kvp.Value));
});
agent.RuleActivationFreshness = new Dictionary <Rule, int>(RuleActivationFreshness);
return(agent);
}
