International audienceIt is known that in chess, random positions are harder to memorize for humans. We here reproduce these experiments in the Asian game of Go, in which computers are much weaker than humans. We survey families of positions, discussing the relative strength of humans and computers, and then experiment random positions. The result is that computers are at the best amateur level for random positions. We also provide a protocol for generating interesting random positions (avoiding unfair situations)
International audienceMonte-Carlo Tree Search and Upper Confidence Bounds pro- vided huge improvement...
International audienceRecently, a methodology has been proposed for boosting the computational intel...
Experts appear able to handle much larger amounts of specialized information than nonexperts, and ha...
International audienceIt is known that in chess, random positions are harder to memorize for humans....
A widely cited result asserts that experts’ superiority over novices in recalling meaningful materia...
Computer Go programs have surpassed top-level human players by using deep learning and reinforcement...
AbstractThis article investigates the application of machine-learning techniques for the task of sco...
This paper explores the question, important to the theory of expert performance, of the nature and n...
International audienceTHE AUTHORS ARE EXTREMELY GRATEFUL TO GRID5000 for helping in designing and ex...
AbstractComputer Go is one of the biggest challenges faced by game programmers. This survey describe...
International audienceIn this paper, we will consider questions related to blindfolded play: (i) the...
International audienceMany artificial intelligences (AIs) are randomized. One can be lucky or unluck...
Go provides artificial intelligence (AI) and cognitive science researchers with an easily specified ...
Although computer Go players are now better than humans on small board sizes, they are still a fair ...
In the recent decade, artificial intelligence of all sorts have revolutionized the highly complex co...
International audienceMonte-Carlo Tree Search and Upper Confidence Bounds pro- vided huge improvement...
International audienceRecently, a methodology has been proposed for boosting the computational intel...
Experts appear able to handle much larger amounts of specialized information than nonexperts, and ha...
International audienceIt is known that in chess, random positions are harder to memorize for humans....
A widely cited result asserts that experts’ superiority over novices in recalling meaningful materia...
Computer Go programs have surpassed top-level human players by using deep learning and reinforcement...
AbstractThis article investigates the application of machine-learning techniques for the task of sco...
This paper explores the question, important to the theory of expert performance, of the nature and n...
International audienceTHE AUTHORS ARE EXTREMELY GRATEFUL TO GRID5000 for helping in designing and ex...
AbstractComputer Go is one of the biggest challenges faced by game programmers. This survey describe...
International audienceIn this paper, we will consider questions related to blindfolded play: (i) the...
International audienceMany artificial intelligences (AIs) are randomized. One can be lucky or unluck...
Go provides artificial intelligence (AI) and cognitive science researchers with an easily specified ...
Although computer Go players are now better than humans on small board sizes, they are still a fair ...
In the recent decade, artificial intelligence of all sorts have revolutionized the highly complex co...
International audienceMonte-Carlo Tree Search and Upper Confidence Bounds pro- vided huge improvement...
International audienceRecently, a methodology has been proposed for boosting the computational intel...
Experts appear able to handle much larger amounts of specialized information than nonexperts, and ha...