“Microsoft researchers have created an artificial intelligence-based system that learned how to get the maximum score on the addictive 1980s video game Ms. Pac-Man, using a divide-and-conquer method that could have broad implications for teaching AI agents to do complex tasks that augment human capabilities. The team from Maluuba, a Canadian deep learning startup acquired by Microsoft earlier this year, used a branch of AI called reinforcement learning to play the Atari 2600 version of Ms. Pac-Man perfectly. Using that method, the team achieved the maximum score possible of 999,990. Doina Precup, an associate professor of computer science at McGill University in Montreal said that’s a significant achievement among AI researchers, who have been using various videogames to test their systems but have found Ms. Pac-Man among the most difficult to crack. But Precup said she was impressed not just with what the researchers achieved but with how they achieved it. To get the high score, the team divided the large problem of mastering Ms. Pac-Man into small pieces, which they then distributed among AI agents.”
Related Content
Related Posts:
- Unlocking the future of computing: The Analog Iterative Machine’s lightning-fast approach to optimization
- Increasing access to education for people with disabilities
- Microsoft, university researchers use AI to aid in study of ancient script on China’s “oracle bones”
- Microsoft open sources its ‘farm of the future’ toolkit
- Open Source Release coming for Microsoft’s Quantum Development Kit
- Learn at your own pace with Microsoft Quantum Katas
- Microsoft and DEWA bringing quantum computing to Dubai
- Microsoft Quantum helps Case Western Reserve University advance MRI research
- Microsoft reaches a historic milestone, using AI to match human performance in translating news from Chinese to English
- Microsoft updates its Quantum Development Kit and adds support for Linux and Mac