public Action getAction(GameState state)
{
var availActions = state.GetActionSet();
var flipCoin = _rand.NextDouble();
if (flipCoin < epsilon)
{
var selected = _rand.Next(availActions.Count());
return availActions.ToList()[selected];
}
else
{
return computeActionFromQValues(state);
}
}
public Action getAction(GameState state)
{
var availActions = state.GetActionSet();
var flipCoin = _rand.NextDouble();
if (flipCoin < epsilon)
{
var selected = _rand.Next(availActions.Count());
return(availActions.ToList()[selected]);
}
else
{
return(computeActionFromQValues(state));
}
}
public Action computeActionFromQValues(GameState state)
{
Action action = Action.NONE;
var value = Double.MinValue;
var availActions = state.GetActionSet();
foreach (var a in availActions)
{
var v = _stateQValueMap[Tuple.Create(state, a)];
if (v > value)
{
action = a;
value = v;
}
}
return action;
}
public Action computeActionFromQValues(GameState state)
{
Action action = Action.NONE;
var value = Double.MinValue;
var availActions = state.GetActionSet();
foreach (var a in availActions)
{
var v = _stateQValueMap[Tuple.Create(state, a)];
if (v > value)
{
action = a;
value = v;
}
}
return(action);
}
private void resetModel()
{
_agent = new QLearningAgent();
trackBarAlpha.Value = 2;
trackBarGamma.Value = 8;
trackBarEpsilon.Value = 1;
_agent.alpha = 0.2;
_agent.gamma = 0.8;
_agent.epsilon = 0.05;
// regiser state-qvalue
foreach (var userHp in Enumerable.Range(0, _maxUserHp + 1))
{
foreach (var userPos in Enumerable.Range(0, _maxUserPos + 1))
{
foreach (var towerHp in Enumerable.Range(0, _maxTowerHp + 1))
{
var state = new GameState(userHp, userPos, towerHp);
var compactState = new CompactGameState(userHp, userPos, towerHp);
foreach (var action in state.GetActionSet())
{
if (checkBoxCompact.Checked)
_agent.registerStateQValue(compactState, action, 0);
else
_agent.registerStateQValue(state, action, 0);
}
}
}
}
}
