{"id":4641,"date":"2020-06-24T14:56:17","date_gmt":"2020-06-24T06:56:17","guid":{"rendered":"http:\/\/pairlabs.ai.pro6.designworks.tw\/?post_type=portfolio&#038;p=4641"},"modified":"2020-07-22T15:27:07","modified_gmt":"2020-07-22T07:27:07","slug":"artificial-intelligence-on-the-assistance-of-learning-board-games-for-human-p-en","status":"publish","type":"portfolio","link":"https:\/\/pairlabs.ai\/en\/portfolio-item\/artificial-intelligence-on-the-assistance-of-learning-board-games-for-human-p-en\/","title":{"rendered":"Artificial Intelligence on the Assistance of Learning Board Games for Human"},"content":{"rendered":"<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_1' class='avia-section main_color avia-section-large avia-no-border-styling avia-full-stretch av-section-color-overlay-active avia-bg-style-fixed    av-small-hide av-mini-hide container_wrap sidebar_right' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  '  data-section-bg-repeat='stretch' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  ' ><div class='av-section-color-overlay-wrap'><div class='av-section-color-overlay' style='opacity: 0.6; background-color: #ffffff; '><\/div><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4641'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding first   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '  style='font-size:20px; '  itemprop=\"text\" ><p style=\"text-align: center;\">Pervasive Artificial Intelligence Research (PAIR) Labs<\/p>\n<\/div><\/section><br \/>\n<div style='height:20px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top    \" style='background-color:#00a0e9; background:linear-gradient(to bottom right,#00a0e9,#25a98f); padding:10px; border-radius:0px; '><p><div style=' margin-top:-21px; margin-bottom:0px;'  class='hr hr-custom hr-center hr-icon-yes   '><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><span class='av-seperator-icon' style='color:#ffffff;' aria-hidden='true' data-av_icon='\ue883' data-av_iconfont='entypo-fontello'><\/span><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  av_inherit_color '  style='font-size:30px; color:#ffffff; '  itemprop=\"text\" ><h1 style=\"text-align: center;\">Computer games Team<\/h1>\n<\/div><\/section><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 -->\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><\/div><div id='after_section_1' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4641'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_2' class='avia-section main_color avia-section-large avia-no-border-styling avia-full-stretch av-section-color-overlay-active avia-bg-style-fixed    av-desktop-hide av-medium-hide container_wrap sidebar_right' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  '  data-section-bg-repeat='stretch' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  ' ><div class='av-section-color-overlay-wrap'><div class='av-section-color-overlay' style='opacity: 0.6; background-color: #ffffff; '><\/div><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4641'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding first   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '  style='font-size:20px; '  itemprop=\"text\" ><p style=\"text-align: center;\">Pervasive Artificial Intelligence Research (PAIR) Labs<\/p>\n<\/div><\/section><br \/>\n<div style='height:1px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top    \" style='background-color:#00a0e9; background:linear-gradient(to bottom right,#00a0e9,#25a98f); padding:10px; border-radius:0px; '><p><div style=' margin-top:-21px; margin-bottom:0px;'  class='hr hr-custom hr-center hr-icon-yes   '><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><span class='av-seperator-icon' style='color:#ffffff;' aria-hidden='true' data-av_icon='\ue883' data-av_iconfont='entypo-fontello'><\/span><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  av_inherit_color '  style='font-size:30px; color:#ffffff; '  itemprop=\"text\" ><h2 style=\"text-align: center;\">Computer games Team<\/h2>\n<\/div><\/section><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 -->\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><\/div><div id='after_section_2' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4641'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_3' class='avia-section socket_color avia-section-default avia-no-border-styling avia-bg-style-scroll    av-arrow-down-section container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4641'><div class='entry-content-wrapper clearfix'>\n<div style='padding-bottom:0px; margin:0 0 0 0; font-size:30px;' class='av-special-heading av-special-heading-h3  blockquote modern-quote modern-centered   av-inherit-size '><h3 class='av-special-heading-tag '  itemprop=\"headline\"  >Artificial Intelligence on the Assistance of Learning Board Games for Human<\/h3><div class='special-heading-border'><div class='special-heading-inner-border' ><\/div><\/div><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><div class='av-extra-border-element border-extra-arrow-down'><div class='av-extra-border-outer'><div class='av-extra-border-inner'  style='background-color:#333333;' ><\/div><\/div><\/div><\/div><div id='after_section_3' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4641'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_4' class='avia-section main_color avia-section-default avia-no-border-styling avia-bg-style-scroll   container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4641'><div class='entry-content-wrapper clearfix'>\n<div class=\"flex_column av_three_fifth  flex_column_div av-zero-column-padding first  \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '   itemprop=\"text\" ><p><b>Principal Investigator:<\/b><a href=\"http:\/\/pairlabs.ai\/\/en\/2018\/04\/21\/professor-shi-jim-yen\/\">Professor Shi-Jim Yen<\/a><\/p>\n<p>&#8212;<\/p>\n<blockquote>\n<h5><b>Summary<\/b><\/h5>\n<\/blockquote>\n<p>The goal of this project is to develop the AI techniques that assists human to learn board games techniques easily and efficiently. Board games training to the field of artificial intelligence is like trials over drosophila to the medical field. A series of AlphaGo and Alpha Zero programs create a history for AI. We believe that computer games will also play the role of the drosophila of computer-assisted learning. Because this project will investigate many kinds of games, it is expected that innovative Deep Learning(DL)\/Reinforcement Learning(RL)\/Deep Reinforcement Learning(DRL) techniques will be developed. In terms of the development of society, with the rise of AI, humans need better logical decision-making ability and critical thinking skills more than ever. Board games are great tools for exercising logical thinking. For children, playing board games helps them develop logical thinking abilities, and cultivates their resilience and perseverance. It is shown by a Gerontology research institute in Japan that Go could improve cognitive functions. As such, this project has positive effects on the development of society.<\/p>\n<blockquote>\n<h5><b>Keywords<\/b><\/h5>\n<\/blockquote>\n<p>Board Game, Alpha Go, Alpha Zero, Deep Learning, Reinforcement Learning, Deep Reinforcement Learning, Residual Network, Generative Adversarial Network, FeUdal networks, Seed Optimization.<\/p>\n<blockquote>\n<h5><b>Innovations<\/b><\/h5>\n<\/blockquote>\n<ul>\n<li>We use DRL to train the models for personalized ladder and visual learning. It could improve the quality of our AI Go services. The services are running on an online AI-assisted board games learning platform for teaching, learning and playing Go. It will be the world\u2019s largest AI Go service with 0.5 billion annual AI service count.<\/li>\n<li>We compress Chinese dark chess endgame databases with DL. This could increase the efficiency of Chinese dark chess programs. The paper is published in IEEE Transactions on Games.<\/li>\n<li>We analyze and develop efficient solutions for 2\u00d74 Chinese dark chess.<\/li>\n<li>We use Seed optimization framework on board games, including Draughts, Othello, and Block Go. The framework could increase the strength of those game programs.<\/li>\n<li>For Board Evaluation research, we successfully developed a new technique called Board Evaluation Multi-Labelled Value Network (BV-ML-VN), and published in IEEE TCIAIG.<\/li>\n<\/ul>\n<blockquote>\n<h5><b>Benefits<\/b><\/h5>\n<\/blockquote>\n<ul>\n<li>Computer board game is considered to be the drosophila of artificial intelligence. In the field of assisting human learning, we believe computer board games can also play the role of the drosophila. By exploring various types of games in this project, we could spark numerous new DL\/RL\/DRL technologies.<\/li>\n<li>We will develop\/achieve the following important objectives:\n<ol>\n<li>Online AI-assisted board games learning platform; teaching, learning and playing system for Go; world\u2019s largest AI Go service website: 0.5 billion annual AI service count.<\/li>\n<li>Deep Learning research applied to Go AI personalities and playing styles; develop over a hundred bots with distinct personalities.<\/li>\n<li>Application to the popularization of Go and AI education; contribute to the the long-term care system; promote social welfare; prevent or slow cognitive impairment.<\/li>\n<\/ol>\n<\/li>\n<li>We collaborate with the Nihon Ki-in (Japan Go Association), and with professional player Ming-wan Wang as consultant, and deploy an ample number of AI Go bots on their UGEN(Yugen no Ma) Go playing website. Currently, these bots are very popular among Japanese players, with over 120 million cumulative service count.<\/li>\n<li>Subproject 1 develops a Go teaching and learning system, and subproject 2 develops a Go learning environment. The system and environment could help people to learn Go techniques easily and efficiently. Subproject 2 also develops systems and environments for Jungo and Block Go. Jungo and Block Go were designed for the beginners of Go.<\/li>\n<li>Subproject 3 develops connection games teaching and learning systems. These connection games include Gomoku, Connect6, and Othello. Subproject 4 develops non-deterministic games teaching and learning systems. These non-deterministic games include Chinese dark chess, Mahjong and 55 dice shogi.<\/li>\n<\/ul>\n<\/div><\/section><\/div><div class=\"flex_column av_two_fifth  flex_column_div av-zero-column-padding   \" style='border-radius:0px; '><p><div class='avia-progress-bar-container  av-desktop-hide av-medium-hide av-small-hide av-mini-hide avia_animate_when_almost_visible   av-striped-bar av-animated-bar '><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 1<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 91%' data-progress='91'><\/div><\/div><\/div><\/div><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 2<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 86%' data-progress='86'><\/div><\/div><\/div><\/div><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 3<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 97%' data-progress='97'><\/div><\/div><\/div><\/div><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 4<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 85%' data-progress='85'><\/div><\/div><\/div><\/div><\/div><br \/>\n<div style='height:20px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<div id='av-masonry-1' class='av-masonry  noHover av-fixed-size av-no-gap av-hover-overlay- av-masonry-animation-active av-masonry-col-2 av-caption-always av-caption-style- av-masonry-gallery   av-orientation-portrait   av-medium-columns-overwrite av-medium-columns-2 av-small-columns-overwrite av-small-columns-2 av-mini-columns-overwrite av-mini-columns-2'  ><div class='av-masonry-container isotope av-js-disabled ' ><div class='av-masonry-entry isotope-item av-masonry-item-no-image '><\/div><a href=\"https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/06\/\u984f\u58eb\u6de8-1-773x1030.jpg\" id='av-masonry-1-item-5180' data-av-masonry-item='5180' class='av-masonry-entry isotope-item post-5180 attachment type-attachment status-inherit hentry  av-masonry-item-with-image' title=\"\u984f\u58eb\u6de8\"  itemprop=\"thumbnailUrl\" ><div class='av-inner-masonry-sizer'><\/div><figure class='av-inner-masonry main_color'><div class=\"av-masonry-outerimage-container\"><div class=\"av-masonry-image-container\" style=\"background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/06\/\u984f\u58eb\u6de8-1-529x705.jpg);\" title=\"\u984f\u58eb\u6de8\" ><\/div><\/div><\/figure><\/a><!--end av-masonry entry--><\/div><\/div><\/p><\/div><\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='after_section_4' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4641'><div class='entry-content-wrapper clearfix'><\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_5' class='avia-section alternate_color avia-section-default avia-no-border-styling avia-bg-style-scroll    container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4641'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class=\"flex_column av_two_fifth  flex_column_table_cell av-equal-height-column av-align-middle av-zero-column-padding first   \" style='border-radius:0px; 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