jsnn/c4_learner.html at master · Nath-R/jsnn · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
<html>
<head>
<title>Connect 4</title>
<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
<meta name="author" content="Nathan Ramoly">

<style>

table
{
	border-spacing: 0px;
	border-collapse: collapse;
}

button
{
	width: 100px;
}

</style>


</head>

<body>

<div id="choice">
<table>
	<td>
		<tr> <button type="button" onclick="human_choice(0)"> V </button> </tr>
		<tr> <button type="button" onclick="human_choice(1)"> V </button> </tr>
		<tr> <button type="button" onclick="human_choice(2)"> V </button> </tr>
		<tr> <button type="button" onclick="human_choice(3)"> V </button> </tr>
		<tr> <button type="button" onclick="human_choice(4)"> V </button> </tr>
		<tr> <button type="button" onclick="human_choice(5)"> V </button> </tr>
		<tr> <button type="button" onclick="human_choice(6)"> V </button> </tr>
	</td>
</table>
</div>

<div id="board">
</div>


<script src="weight.js"></script>
<script src="neuron.js"></script>
<script src="neuronLayer.js"></script>
<script src="neuronNetwork.js"></script>

<script type="text/javascript">

/** POWER 4 ENGINE & ANN TRAINER **/

//Board, array of double dimension ( [row][line] ), from left to right and bottom to top
//Dimension 6*7
//0: empty;  1: player 1; 2: player 2
var board;
//Init
board = new Array(7);
for(var i=0; i<7; i++)
{
	board[i] = new Array(6);
	for(var j=0; j<6; j++)
	{
		board[i][j] = 0;
	}
}

//For human choice management
var choiceNeeded;
var choiceDone;
var choice;

//Meta game management
var game_nbr = 0;
var run_size = 10; //10 by 10 to select the weight
var max_game_nbr = 1000;

//ANN management
var nnStruct = [84, 84, 7];
var listSize = 10;
var threshold = 0.3;
var nnList = new Array(listSize);
var nnScore = new Array(listSize);

//Number of turn of a game
var turn = 0;
//Number of failed turn, to select the next choice. Reset between each turn
var failed_turn = 0;

//Methods

/**
 * Reinit the list of neural network
 */
 function init_ann()
 {
	for(var i=0; i<listSize; i++)
	{
		var weightSet = new Weight();
		weightSet.init_random(nnStruct);

		nnList[i] = new NeuronNetwork();
		nnList[i].init(weightSet, threshold);

		nnScore[i] = 0;
	}
 }

/**
 * Select the best previous ann and create the new generation.
 */
 function new_generation()
 {
	var bestAnn = 0;

	for(var i=0; i<listSize; i++)
	{
		if( nnScore[i] > nnScore[bestAnn] )
		{
			bestAnn = i;
		}
	}

	//Create the new generation...
	//Two first are the two previous best
	var ann = nnList[bestAnn];
	nnList[0] = ann;
	nnList[1] = ann;

	//The rest: evolution of the two other
	for(var i=2; i<listSize; i++)
	{
		var weightSet = new Weight();
		weightSet.init_evolve(ann.get_weights().serialize() , 0.25);

		nnList[i] = new NeuronNetwork();
		nnList[i].init(weightSet, threshold);
	}

	//Clear the score
	for(var i=0; i<listSize; i++)
	{
		nnScore[i] = 0;
	}
 }

 /**
  * Get the current best ann
  */
 function get_best_ann()
 {
	var bestAnn = 0;

	for(var i=0; i<listSize; i++)
	{
		if( nnScore[i] > nnScore[bestAnn] )
		{
			bestAnn = i;
		}
	}

	return nnList[bestAnn];
 }

/**
 * Reinit the board
 */
 function init_board()
 {
	for(var i=0; i<7; i++)
	{
		for(var j=0; j<6; j++)
		{
			board[i][j] = 0;
		}
	}

	//Reprint
	print_board();
 }


/**
 * Putting a token in the wanted row for a given player
 * return true if token has been added, false otherwise.
 */
function add_token( player, row )
{
	if( !(player == 1 || player == 2) || row < 0 || row > 6 )
	{return false;}

	//Going through from the bottom to the top and taking the first empty one
	for(var i=0; i<6; i++)
	{
		if( board[row][i] == 0 )
		{
			board[row][i] = player;
			return true;
		}
	}

	//No room for a new token !
	return false;
}

/**
 * Print the power 4 board as a table in html
 */
 function print_board()
 {
	var html = "";

	html += "<table>";

	//Going though line
	for(var l=5; l>=0; l--)
	{
		html += "<tr>";

		//Going though column
		for(var c=0; c<7; c++)
		{
			html += "<td>";

			if(board[c][l]==1)
			{ html += "<img src='images/p4_red.png' width=100 height=100>"; }
			else if(board[c][l]==2)
			{ html += "<img src='images/p4_yellow.png' width=100 height=100>"; }
			else
			{ html += "<img src='images/p4_empty.png' width=100 height=100>"; }

			html += "</td>";
		}

		html += "</tr>";
	}

	html += "</table>";

	//Dispplay
	document.getElementById('board').innerHTML = html;

 }

 /**
  * Run a power 4 run
  */
 function connect4()
 {
	//Init
	init_board();

	//Turn number
	turn = 0;

	//Start the main loop...
	setTimeout(next_turn, 0);
 }

 /**
  * End of the game
  */
 function connect4_end( res )
 {
	//Compute score of the current ann:  score = number max of turn less the number of turn needed, inverses if defeat.
	nnScore[(game_nbr % run_size)] = (42 - turn) * Math.pow(-1, res);

	console.log(res+" en "+turn+" tours, score: "+nnScore[(game_nbr % run_size)]);
	game_nbr++;

	if( (game_nbr % run_size) != 0 )
	{ connect4(); }
	else
	{ end_run(); }
 }


 /**
  * Do the next turn
  */
 function next_turn()
 {
	//Do one turn..
	player = turn%2 + 1;

	//Get movement
	if(player == 1)
	{ request_random_choice(); }
	else if(player == 2)
	{ request_ann_choice(); }
 }

 function end_turn()
 {
	var turnOk = add_token(player, choice);

	//Restart turn if not valid
	if(!turnOk)
	{
		failed_turn++;
		setTimeout(next_turn, 0);
	}
	else
	{
		turn++;

		failed_turn = 0;

		print_board();

		//Check if over or not
		var res = check(choice);
		if( res == -1) // not finished
		{ setTimeout(next_turn, 0); }
		else
		{ connect4_end(res); }
	}
 }


 /**
  * Wait for a human choice
  */
 function request_human_choice()
 {
	choiceNeeded = true;
 }

 /**
  * A random choice
  */
 function request_random_choice()
 {
	choice = Math.floor( Math.random()*7 );
	setTimeout(end_turn, 100);
 }

 /**
  * Use the neural network to make a choice
  */
 function request_ann_choice()
 {
	//Setting the input array
	var inputArray = new Array(84);
	for(var i=0; i<42; i++)
	{
		var content = board[Math.floor(i/7)][i%7]
		if(content == 1)
		{ inputArray[i] = 1; }
		else
		{ inputArray[i] = 0; }

		if(content == 2)
		{ inputArray[42+i] = 1; }
		else
		{ inputArray[42+i] = 0; }
	}

	var resList = nnList[(game_nbr % run_size)].compute_result(inputArray);

	//Sorting the list, then read from the last one. To get the position we go thorugh the previous list and compare with the selected value
	var sortedList = resList.slice(0);
	sortedList.sort();

	choice = 0;

	for(var i=0; i<7; i++)
	{
		if( resList[i] == sortedList[6-failed_turn] )
		{
			prev_value = resList[i];
			choice = i;
		}
	}

	setTimeout(end_turn, 100);
 }

 /**
  * A human choice
  * Not used in this training program
  */
 function human_choice(row)
 {
	if(choiceNeeded)
	{
		choiceNeeded = false;
		choice = row;
		setTimeout(end_turn, 0);
	}
 }

 /**
  * Check if the game is over or not.
  * It take the last row selected (and find the line by taking the first one from the top)
  * return -1 if not ended, 0 if draw, 1 if player 1 won, 2 if player 2 won
  */
 function check(lastRow)
 {
	var row = lastRow;
	var line;
	var found = false;
	var team = 0; //Team to check
	var count = 0; //to count the rumbered of aligned token

	//Finding the last ligne
	for(var i=5; i>=0 && !found; i--)
	{
		if(board[row][i] != 0)
		{
			line = i;
			team = board[row][i];
			found = true;
		}
	}

	//ERROR
	if(team == 0)
	{ alert("Unable to check !"); return; }

	//Check horizontally
	count = 0;
	for(var i=0; i<7; i++)
	{
		if(board[i][line] == team)
		{ count++; }
		else
		{ count = 0; }

		if(count >= 4)
		{ return team; }
	}

	//Check vertically
	count = 0;
	for(var i=0; i<7; i++)
	{
		if(board[row][i] == team)
		{ count++; }
		else
		{ count = 0; }

		if(count >= 4)
		{ return team; }
	}

	//Check diagonal (left to right)
	//Taking a start (out of the board, but osef)
	//Not opitimized, but idgaf (diagonal, mas lenght: 6)
	var step = Math.min( (row),( 5 - line) );
	var startRow = row - step;
	var startLine = line + step;
	count = 0;
	for(var i=0; i<6; i++)
	{
		if( 0 <= startRow+i && startRow+i < 7 && 0 <= startLine-i && startLine-i < 6 )
		{
			if(board[startRow+i][startLine-i] == team)
			{ count++; }
			else
			{ count = 0; }

			if(count >= 4)
			{ return team; }
		}
	}

	//Diagonal ( right to left)
	step = Math.min( (6-row),(5-line) );
	startRow = row + step;
	startLine = line + step;
	count = 0;
	for(var i=0; i<6; i++)
	{
		if( 0 <= startRow-i && startRow-i < 7 && 0 <= startLine-i && startLine-i < 6 )
		{
			if(board[startRow-i][startLine-i] == team)
			{ count++; }
			else
			{ count = 0; }

			if(count >= 4)
			{ return team; }
		}
	}


	//Check if all token has been set
	if(turn >= 42)
	{ return 0; }

	//It's not over yet !!
	return -1;
 }

 /**
  * Management between too run:
  * Make the ann evolve by taking the better one.
  */
 function end_run()
 {
	console.log("Run ended...")
	//Check the score for each one
	//And get the most efficient set


	//Launch next run
	if( game_nbr < max_game_nbr )
	{
		new_generation();
		connect4();
	}
	else
	{
		alert("Training done, see the console to get the current ANN");
		//Return current ANN
		console.log( get_best_ann().get_weights().serialize() );
	}
 }

 //First display
 print_board();

 //First ann set
 init_ann();

 //Launching the first game
 connect4();

</script>


</body>
</html>