Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, ...
The idea that machines can make intelligent decisions has been around since the 1950s when the first learning programme was built. At the time, the machine itself was groundbreaking, improving at the game of checkers the more it played. Since then, the idea of such machines has become more and more ...
It's time to take on artificial intelligence (AI) in our "How to Speak Like a Data Center Geek" series. Because even though it's been around for six decades, AI has rarely been hotter. In Equinix's 2018 predictions, we forecast an imminent AI breakthrough into the mainstream. As fast as it's moving, AI isn't approaching the dark vision presented by popular culture (HAL 9000, meet The Matrix) or the expectations of more optimistic thinkers who say it will usher in a new era of human civilization … yet. But who knows what's ahead?
CHINOOK that I also highly recommend. AI Magazine Volume 20 Number 1 (1999) ( AAAI) vided more than a glimpse of the intense process it described. One Jump Ahead was written by the person most involved in the process. Thus, it provides us with a direct view of Schaeffer's maturation--a maturation that we should all hope to have. Schaeffer does not pull any punches in his book; we see many of his elations, his disappointments, and his flaws.
Samuel's successes included a victory by his program over a master-level player. In fact, the opponent was not a master, and Samuel himself had no illusions about his program's strength. This single event, a milestone in AI, was magnified out of proportion by the media and helped to create the impression that checkers was a solved game. Nevertheless, his work stands as a major achievement in machine learning and AI. Since 1950, the checkers world has been dominated by Tinsley.
Arthur Samuel (1901-1990) was a pioneer of artificial intelligence research. From 1949 through the late 1960s, he did the best work in making computers learn from their experience. His vehicle for this work was the game of checkers. Programs for playing games often fill the role in artificial intelligence research that the fruit fly Drosophila plays in genetics. Drosophilae are convenient for genetics because they breed fast and are cheap to keep, and games are convenient for artificial intelligence because it is easy to compare a computer's performance on games with that of a person.
Trustees to honor senior scientists in artificial intelligence for contributions and service to the field during their careers. The Award carries a stipend of $1,000 and covers expenses of the recipient's attendance at Distinguished Service Award; the first was presented to Bernard Meltzer in 1979. Arthur Samuel is one of the pioneeers in AI. His checkers program was the earliest high-performance AI system, and his work on machine learning is a classic in the field.
This work remains a milestone in AI research. Samuel's program reportedly beat a master and "solved" the game of checkers. Both journalistic claims were false, but they created the impression that there was nothing of scientific interest left in the game (Samuel himself made no such claims). Consequently, most subsequent game-related research turned to chess. Other than a program from Duke University in the 1970s (Truscott 1979), little attention was paid to achieving a world championship-caliber checker program.
AI Game-Playing Techniques: Are They Useful for Anything Other Than Games? In conjunction with the American Association for Artificial Intelligence's Hall of Champions exhibit, the Innovative Applications of Artificial Intelligence held a panel discussion entitled "AI Game-Playing Techniques: Are They Useful for Anything Other Than Games?" This article summarizes the panelists' comments about whether ideas and techniques from AI game playing are useful elsewhere and what kinds of game might be suitable as "challenge problems" for future research. AAAI-98's Hall of Champions exhibit) is an AI games researcher at the University of Alberta and author of the checkers program The early research on the alpha-beta search algorithm was useful in establishing a foundation for AI theories of heuristic search, and these theories have been useful in many areas of AI. Several of the panelists (particularly Schaeffer, Wilkins, and Fotland) pointed out that the minimax search algorithms traditionally associated with AI have only a limited range of applicability.