Benjamin Franklin wrote a book about chess. Napoleon spent his post-Waterloo years in exile playing chess on St. Helena. John Wayne carried a set and played during downtime while filming “El Dorado.”
“Chess can be addictive,” Dimitri Bertsekas says.
Long before Bertsekas became a luminary in mathematics and computer science, authoring foundational textbooks on reinforcement learning, a type of artificial intelligence, or AI, he was an undergraduate with a passion for chess.
“I was playing all the time and missing classes,” he says, jokingly. “I ultimately decided I wanted to be a mathematician more than a chess player and for a while I gave up the game.”
Bertsekas explains the attraction.
“Games are designed to challenge human intelligence,” he says. “So, they are a good way to also demonstrate the intelligence of an artificial system.”
He adds that games tend to have well-known, fixed rules which means that the results are socially well understood, saying, “We all know what it means to win or to lose a game.”
Now Bertsekas, a member of the National Academy of Engineering, and a professor in the School of Computing and Augmented Intelligence, part of the Ira A Fulton Schools of Engineering at Arizona State University, has found a way to combine his lifelong passion for chess with his expertise for developing new forms of innovative AI.
Working with Yuchao Li, a Fulton Schools postdoctoral research scholar, and Atharva Gundawar, an ASU computer science graduate student, he has created a meta-algorithm that leverages the outputs of multiple top chess engines. An algorithm is a set of instructions that a computer follows to complete its work while a meta-algorithm is a type of AI where one system learns from another system’s algorithms.
Bertsekas, Li and Gundawar have published their findings in the paper “Superior Computer Chess with Model Predictive Control, Reinforcement Learning, and Rollout” and are seeking a patent for the new technology.
The meta-algorithm has other potentially far-reaching applications in areas such as automated transportation, health care and cybersecurity.
Read the full story on Full Circle.