Exemple #1
0
    /// <summary>
    /// Creates the children of this node with a given new piece
    /// </summary>
    /// <param name="newCurrentPiece"></param>
    public void ExtendNode(PieceModel newCurrentPiece)
    {
        List <PieceAction> actions = state.GetActions(newCurrentPiece);

        foreach (PieceAction action in actions) //Each child is related with one of the possible actions for the newCurrentPiece played in the state of this node
        {
            TetrisState newState = state.CloneState();
            newState.DoAction(newCurrentPiece, action);

            newCurrentPiece.ResetCoordinates();

            MCTSNode newNode = new MCTSNode(MCTreeSearch.nNodes, this, newState, action, newCurrentPiece);
            children.Add(newNode);
        }
    }
Exemple #2
0
    /// <summary>
    /// Main bot method that searches for the best action to do with the current piece in the current state.
    /// It has a budget of time which is the max time it has to find that best action
    /// </summary>
    /// <param name="nextPieceType"></param>
    /// <param name="budget"></param>
    /// <returns></returns>
    public virtual IEnumerator ActCoroutine(PieceType nextPieceType, float budget)
    {
        float t0 = 0.0f;

        PieceModel nextPiece = new PieceModel(nextPieceType);

        List <PieceAction> possibleActions; //First of all, it gets the possible actions with the current piece in the current state

        if (!pieceActionDictionary.ContainsKey(nextPieceType))
        {
            possibleActions = emptyTetrisState.GetActions(nextPiece);
            pieceActionDictionary.Add(nextPieceType, possibleActions);
        }
        else
        {
            possibleActions = pieceActionDictionary[nextPieceType];
        }

        float       bestScore = -float.MaxValue;
        PieceAction bestAction;

        int i            = Random.Range(0, possibleActions.Count); //The first possible action to test is chosen randomly
        int initialIndex = i;

        bestAction = possibleActions[i];

        yield return(null);

        t0 += Time.deltaTime;

        //In a while loop that goes until the time ends
        while (t0 < budget && i < possibleActions.Count)
        {
            if (!TBController.pausedGame)
            {
                t0 += Time.deltaTime;

                TetrisState newState = currentTetrisState.CloneState(); //The TetrisState is cloned

                newState.DoAction(nextPiece, possibleActions[i]);       //One of the possible actions is played in the cloned state
                nextPiece.ResetCoordinates();

                float score = newState.GetScore(); //And its score is got

                if (score > bestScore)
                {
                    bestScore  = score;
                    bestAction = possibleActions[i];
                }

                i++;

                if (i == possibleActions.Count)
                {
                    i = 0;
                }
                if (i == initialIndex)
                {
                    break;                    //If all the possible actions have been tested, the while loop ends
                }
            }

            yield return(null);
        }

        currentTetrisState.DoAction(nextPiece, bestAction); //The bestAction is played in the real state

        TBController.DoActionByBot(bestAction);             //And also, it is said to the TetrisBoardController to play that action in the real board
    }