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index.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Othello JS</title>
<link href="vendor/twitter-bootstrap/css/bootstrap.min.css" rel="stylesheet">
<link href="vendor/twitter-bootstrap/css/bootstrap-responsive.min.css" rel="stylesheet">
<link href="app.css" rel="stylesheet">
</head>
<body>
<div class="navbar navbar-inverse">
<div class="navbar-inner">
<div class="container">
<a class="brand" href=".">Othello JS</a>
<div class="nav-collapse collapse">
<ul class="nav">
<li class="active"><a href=".">Home</a></li>
<li><a href="https://github.com/gzc9047/othello-js">Code</a></li>
</ul>
</div>
</div>
</div>
</div>
<div id="main" class="container">
<div id="game-board"></div>
<div id="current-player">Current player: <span id="current-player-name">-</span></div>
<div id="message"></div>
<div id="game-dump-barrier"></div>
<div id="game-dump-step"></div>
<div id="console"></div>
<div id="stats"></div>
<div id="rollback">
<button id="rollback-one-step-button" class="btn" type="button">Rollback one step</button>
</div>
<div id="preference-pane">
<div id="player-type-forms">
<label>
Black:
<select id="black-player-type">
<option value="human" selected>Human</option>
<option value="simpleCount-131072">AI (Type A; try to get many disks)</option>
<option value="basic-131072">AI (Type B; try to own corner positions)</option>
<option value="better-131072">AI (Type C; try to own corner positions carefully)</option>
<option value="moveCount-131072">AI (Type D; Prioritize number of moves)</option>
<option value="moveCountAndPositions-131072">AI (Type E; Prioritize number of moves and positions)</option>
<option value="mcts-128">AI (Type M-128; Monte Carlo Tree Search with 128 iterations)</option>
<option value="mcts-256">AI (Type M-256; Monte Carlo Tree Search with 256 iterations)</option>
<option value="mcts-512">AI (Type M-512; Monte Carlo Tree Search with 512 iterations)</option>
<option value="mcts-1024">AI (Type M-1024; Monte Carlo Tree Search with 1024 iterations)</option>
<option value="mcts-2048">AI (Type M-2048; Monte Carlo Tree Search with 2048 iterations)</option>
<option value="mcts-4096">AI (Type M-4096; Monte Carlo Tree Search with 4096 iterations)</option>
<option value="mcts-1024-old">AI (Type M-1024/old; Monte Carlo Tree Search with 1024 iterations)</option>
<option value="pmc-100-m">AI (Type PM-100/m; Primitive Monte Carlo with 100 iterations for each move)</option>
<option value="pmc-200-m">AI (Type PM-200/m; Primitive Monte Carlo with 200 iterations for each move)</option>
<option value="pmc-1024-e">AI (Type PM-1024/e; Primitive Monte Carlo with 1024 iterations divided for each move)</option>
</select>
</label>
<label>
White:
<select id="white-player-type">
<option value="human" selected>Human</option>
<option value="simpleCount-131072">AI (Type A; try to get many disks)</option>
<option value="basic-131072">AI (Type B; try to own corner positions)</option>
<option value="better-131072">AI (Type C; try to own corner positions carefully)</option>
<option value="moveCount-131072">AI (Type D; Prioritize number of moves)</option>
<option value="moveCountAndPositions-131072">AI (Type E; Prioritize number of moves and positions)</option>
<option value="mcts-128">AI (Type M-128; Monte Carlo Tree Search with 128 iterations)</option>
<option value="mcts-256">AI (Type M-256; Monte Carlo Tree Search with 256 iterations)</option>
<option value="mcts-512">AI (Type M-512; Monte Carlo Tree Search with 512 iterations)</option>
<option value="mcts-1024">AI (Type M-1024; Monte Carlo Tree Search with 1024 iterations)</option>
<option value="mcts-2048">AI (Type M-2048; Monte Carlo Tree Search with 2048 iterations)</option>
<option value="mcts-4096">AI (Type M-4096; Monte Carlo Tree Search with 4096 iterations)</option>
<option value="mcts-1024-old">AI (Type M-1024/old; Monte Carlo Tree Search with 1024 iterations)</option>
<option value="pmc-100-m">AI (Type PM-100/m; Primitive Monte Carlo with 100 iterations for each move)</option>
<option value="pmc-200-m">AI (Type PM-200/m; Primitive Monte Carlo with 200 iterations for each move)</option>
<option value="pmc-1024-e">AI (Type PM-1024/e; Primitive Monte Carlo with 1024 iterations divided for each move)</option>
</select>
</label>
</div>
<button id="swap-player-types-button" class="btn" type="button">⇅</button>
<div>
<label>
<input type="radio" name="game-type" value="random-barrier" checked="checked">
Random barrier number:
<select id="random-barrier-number">
<option value="0">0</option>
<option value="1">1</option>
<option value="2">2</option>
<option value="3">3</option>
<option value="4">4</option>
<option value="5" selected>5</option>
</select>
</label>
<label>
<input type="radio" name="game-type" value="restore-game">
Restore game with barrier location and steps, use 8c,d7,3f as the location input.
<br/>
Barrier locations:
<input id="barrier-location" type="text" value="">
<br/>
History steps:
<input id="history-step" type="text" value="">
</label>
</div>
<div>
<input id="new-ai-url" type="text" value="http://gzc9047.github.io/othello-js/random-ai.js">
<button id="add-new-ai-button" class="btn" type="button">Add new AI</button>
</div>
<div>
<label>
<input id="repeat-games" type="checkbox">
Repeat games
</label>
</div>
<button id="start-button" class="btn btn-primary" type="submit">Start a new game</button>
</div>
</div>
<script src="vendor/jquery/jquery-1.9.1.min.js"></script>
<script src="vendor/twitter-bootstrap/js/bootstrap.min.js"></script>
<script src="othello.js"></script>
<script src="app.js"></script>
</body>
</html>