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simple TicTacToe example

/tic-tac-toe
Chris Elion 4 年前
当前提交
f5bf6e08
共有 13 个文件被更改,包括 782 次插入0 次删除
  1. 8
      Project/Assets/ML-Agents/Examples/TicTacToe.meta
  2. 33
      config/ppo/TicTacToe.yaml
  3. 8
      Project/Assets/ML-Agents/Examples/TicTacToe/Scenes.meta
  4. 375
      Project/Assets/ML-Agents/Examples/TicTacToe/Scenes/TicTacToe.unity
  5. 7
      Project/Assets/ML-Agents/Examples/TicTacToe/Scenes/TicTacToe.unity.meta
  6. 8
      Project/Assets/ML-Agents/Examples/TicTacToe/Scripts.meta
  7. 116
      Project/Assets/ML-Agents/Examples/TicTacToe/Scripts/TicTacToeAgent.cs
  8. 11
      Project/Assets/ML-Agents/Examples/TicTacToe/Scripts/TicTacToeAgent.cs.meta
  9. 205
      Project/Assets/ML-Agents/Examples/TicTacToe/Scripts/TicTacToeGame.cs
  10. 11
      Project/Assets/ML-Agents/Examples/TicTacToe/Scripts/TicTacToeGame.cs.meta

8
Project/Assets/ML-Agents/Examples/TicTacToe.meta


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33
config/ppo/TicTacToe.yaml


behaviors:
TicTacToe:
trainer_type: ppo
hyperparameters:
batch_size: 128
buffer_size: 2048
learning_rate: 0.0003
beta: 0.005
epsilon: 0.2
lambd: 0.95
num_epoch: 3
learning_rate_schedule: constant
network_settings:
normalize: false
hidden_units: 512
num_layers: 2
vis_encode_type: simple
reward_signals:
extrinsic:
gamma: 0.99
strength: 1.0
keep_checkpoints: 5
max_steps: 50000
time_horizon: 16
summary_freq: 1000
threaded: false
self_play:
save_steps: 5000
team_change: 20000
swap_steps: 200
window: 10
play_against_latest_model_ratio: 0.5
initial_elo: 1200.0

8
Project/Assets/ML-Agents/Examples/TicTacToe/Scenes.meta


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375
Project/Assets/ML-Agents/Examples/TicTacToe/Scenes/TicTacToe.unity


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116
Project/Assets/ML-Agents/Examples/TicTacToe/Scripts/TicTacToeAgent.cs


using System;
using System.Collections;
using System.Collections.Generic;
using System.Linq;
using UnityEngine;
using Unity.MLAgents;
using Unity.MLAgents.Actuators;
using Unity.MLAgents.Sensors;
public enum PlayerType
{
PlayerX,
PlayerO
}
public class TicTacToeAgent : Agent
{
public PlayerType playerType;
private TicTacToeGame m_Game;
private System.Random m_Random;
// Start is called before the first frame update
void Start()
{
m_Game = GetComponentInParent<TicTacToeGame>();
m_Random = new System.Random(GetInstanceID());
}
public override void CollectObservations(VectorSensor sensor)
{
var rows = m_Game.Board.GetLength(0);
var cols = m_Game.Board.GetLength(1);
for (int r = 0; r < rows; r++)
{
for (int c = 0; c < cols; c++)
{
// One-hot encoding of the board state *depending on the agent's player type*
// Set the 0th element if the board is empty
// Set the 1st element if the board is my type
// Set the 2nd element if the board is my opponent's type
BoardStatus boardVal = m_Game.Board[r, c];
bool isMine = (boardVal == BoardStatus.FilledX && playerType == PlayerType.PlayerX) ||
(boardVal == BoardStatus.FilledO && playerType == PlayerType.PlayerO);
int oneHotIndex = (boardVal == BoardStatus.Empty) ? 0 : (isMine) ? 1 : 2;
sensor.AddOneHotObservation(oneHotIndex, 3);
}
}
}
public override void WriteDiscreteActionMask(IDiscreteActionMask actionMask)
{
var rows = m_Game.Board.GetLength(0);
var cols = m_Game.Board.GetLength(1);
int i = 0;
for (int r = 0; r < rows; r++)
{
for (int c = 0; c < cols; c++)
{
BoardStatus boardVal = m_Game.Board[r, c];
// Disallow moves on non-empty squares
if (boardVal != BoardStatus.Empty)
{
actionMask.WriteMask(0, new[] { i });
}
i++;
}
}
}
public override void OnActionReceived(ActionBuffers actions)
{
var rows = m_Game.Board.GetLength(0);
var index = actions.DiscreteActions[0];
var r = index / rows;
var c = index % rows;
// The trainer can occasionally (about 1 in a million steps) select an invalid move.
// So make sure to check the square is empty before setting it.
if (m_Game.Board[r, c] == BoardStatus.Empty)
{
m_Game.Board[r, c] = (playerType == PlayerType.PlayerX)
? BoardStatus.FilledX
: BoardStatus.FilledO;
}
}
public override void Heuristic(in ActionBuffers actionsOut)
{
// Pick a random empty square.
var validMoves = new List<int>();
var rows = m_Game.Board.GetLength(0);
var cols = m_Game.Board.GetLength(1);
int i = 0;
for (int r = 0; r < rows; r++)
{
for (int c = 0; c < cols; c++)
{
if (m_Game.Board[r, c] == BoardStatus.Empty)
{
validMoves.Add(i);
}
i++;
}
}
var choice = validMoves[m_Random.Next(validMoves.Count)];
var discreteActions = actionsOut.DiscreteActions;
discreteActions[0] = choice;
}
}

11
Project/Assets/ML-Agents/Examples/TicTacToe/Scripts/TicTacToeAgent.cs.meta


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205
Project/Assets/ML-Agents/Examples/TicTacToe/Scripts/TicTacToeGame.cs


using System;
using System.Collections;
using System.Collections.Generic;
using Unity.MLAgents;
using UnityEngine;
public enum BoardStatus
{
Empty,
FilledX,
FilledO
}
public enum WinState
{
NoWinnerYet,
WinnerX,
WinnerO,
Draw
}
public class TicTacToeGame : MonoBehaviour
{
public BoardStatus[,] Board = new BoardStatus[3, 3];
private PlayerType m_CurrentPlayer = PlayerType.PlayerX;
private TicTacToeAgent m_AgentX;
private TicTacToeAgent m_AgentO;
// Start is called before the first frame update
void Start()
{
Academy.Instance.AutomaticSteppingEnabled = false;
var agents = GetComponentsInChildren<TicTacToeAgent>();
foreach (var agent in agents)
{
if (agent.playerType == PlayerType.PlayerX)
{
m_AgentX = agent;
}
else if (agent.playerType == PlayerType.PlayerO)
{
m_AgentO = agent;
}
else
{
throw new UnityAgentsException("Unknown player type.");
}
}
Debug.Assert(m_AgentX != null);
Debug.Assert(m_AgentO != null);
}
void InitBoard()
{
var rows = Board.GetLength(0);
var cols = Board.GetLength(1);
for (int r = 0; r < rows; r++)
{
for (int c = 0; c < cols; c++)
{
Board[r, c] = BoardStatus.Empty;
}
}
}
// Update is called once per frame
void Update()
{
Agent currentAgent = (m_CurrentPlayer == PlayerType.PlayerX) ? m_AgentX : m_AgentO;
currentAgent.RequestDecision();
Academy.Instance.EnvironmentStep();
var winState = CheckForWin();
if (winState == WinState.NoWinnerYet)
{
// Swap
m_CurrentPlayer = m_CurrentPlayer == PlayerType.PlayerX ? PlayerType.PlayerO : PlayerType.PlayerX;
}
else
{
//Debug.Log(this.ToString());
float rewardX = 0.0f;
float rewardO = 0.0f;
if (winState == WinState.WinnerX)
{
rewardX = 1.0f;
rewardO = -1.0f;
//Debug.Log("X wins!");
}
else if (winState == WinState.WinnerO)
{
rewardX = -1.0f;
rewardO = 1.0f;
//Debug.Log("O wins!");
}
else
{
//Debug.Log("Nobody wins :(");
}
m_AgentX.AddReward(rewardX);
m_AgentX.EndEpisode();
m_AgentO.AddReward(rewardO);
m_AgentO.EndEpisode();
InitBoard();
}
}
public WinState CheckForWin()
{
// Assume 3 rows and columns for now, not interested in generalizing.
// Check rows
for (var r = 0; r < 3; r++)
{
if (Board[r, 0] == BoardStatus.Empty)
{
continue;
}
if (Board[r, 1] == Board[r, 0] && Board[r, 2] == Board[r, 0])
{
// all the same in the row
return (Board[r, 0] == BoardStatus.FilledX) ? WinState.WinnerX : WinState.WinnerO;
}
}
for (var c = 0; c < 3; c++)
{
if (Board[0, c] == BoardStatus.Empty)
{
continue;
}
if (Board[1, c] == Board[0, c] && Board[2, c] == Board[0, c])
{
// all the same in the column
return (Board[0, c] == BoardStatus.FilledX) ? WinState.WinnerX : WinState.WinnerO;
}
}
// Check diagonals
{
if (Board[0, 0] == Board[1, 1] && Board[0, 0] == Board[2, 2] && Board[0, 0] != BoardStatus.Empty)
{
return (Board[0, 0] == BoardStatus.FilledX) ? WinState.WinnerX : WinState.WinnerO;
}
if (Board[0, 2] == Board[1, 1] && Board[0, 2] == Board[2, 0] && Board[0, 2] != BoardStatus.Empty)
{
return (Board[0, 2] == BoardStatus.FilledX) ? WinState.WinnerX : WinState.WinnerO;
}
}
// No winner, check if there are still moves or it's a draw
for (var r = 0; r < 3; r++)
{
for (var c = 0; c < 3; c++)
{
if (Board[r, c] == BoardStatus.Empty)
{
return WinState.NoWinnerYet;
}
}
}
// No winner, no empty squares, do it's a draw
return WinState.Draw;
}
static string BoardStatusToString(BoardStatus s)
{
switch (s)
{
case BoardStatus.Empty:
return ".";
case BoardStatus.FilledX:
return "X";
case BoardStatus.FilledO:
return "O";
default:
throw new ArgumentOutOfRangeException(nameof(s), s, null);
}
}
public override string ToString()
{
var b00 = BoardStatusToString(Board[0, 0]);
var b01 = BoardStatusToString(Board[0, 1]);
var b02 = BoardStatusToString(Board[0, 2]);
var b10 = BoardStatusToString(Board[1, 0]);
var b11 = BoardStatusToString(Board[1, 1]);
var b12 = BoardStatusToString(Board[1, 2]);
var b20 = BoardStatusToString(Board[2, 0]);
var b21 = BoardStatusToString(Board[2, 1]);
var b22 = BoardStatusToString(Board[2, 2]);
return $"\n{b00}{b01}{b02}\n{b10}{b11}{b12}\n{b20}{b21}{b22}";
}
}

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Project/Assets/ML-Agents/Examples/TicTacToe/Scripts/TicTacToeGame.cs.meta


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