Monday, June 25, 2018
Search
  
Submit your own News for
inclusion in our Site.
Click here...
Breaking News
FCC to Seek for Flexible Use of C-band and 6GHz Airwaves
AMD Presents Modular Routing Design for Chiplet-based Systems
Software Business Continues to Work For BlackBerry
Apple Turns to the U.S. Patent Office to Invalidate Qualcomm Patents
Samsung Patents Bezel-less, Notch-free Smartphone Design
China is Home to Most Smartphone Vendors
VidCon 2018: Youtube Announces Memberships, Merchandise as Alternatives to Ads
Chatting With Google Assistant Gets More Natural
Active Discussions
Which of these DVD media are the best, most durable?
How to back up a PS2 DL game
Copy a protected DVD?
roxio issues with xp pro
Help make DVDInfoPro better with dvdinfomantis!!!
menu making
Optiarc AD-7260S review
cdrw trouble
 Home > News > General Computing > Microso...
Last 7 Days News : SU MO TU WE TH FR SA All News

Wednesday, June 14, 2017
Microsoft AI Masters Pac-Man


To master the game Ms. Pac-Man, Microsoft researchers have created an artificial intelligence-based system that learned how to get the maximum score on the legendary 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.

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. That's similar to some theories of how the brain works, and it could have broad implications for teaching AIs to do complex tasks with limited information.

The method, which the Maluuba team calls Hybrid Reward Architecture, used more than 150 agents, each of which worked in parallel with the other agents to master Ms. Pac-Man. For example, some agents got rewarded for successfully finding one specific pellet, while others were tasked with staying out of the way of ghosts.

Then, the researchers created a top agent who took suggestions from all the agents and used them to decide where to move Ms. Pac-Man. The top agent took into account how many agents advocated for going in a certain direction, but it also looked at the intensity with which they wanted to make that move. For example, if 100 agents wanted to go right because that was the best path to their pellet, but three wanted to go left because there was a deadly ghost to the right, it would give more weight to the ones who had noticed the ghost and go left.

Harm Van Seijen, a research manager with Maluuba who is the lead author of a new paper about the achievement, said the best results were achieved when each agent acted very egotistically - for example, focused only on the best way to get to its pellet - while the top agent decided how to use the information from each agent to make the best move for everyone.

Rahul Mehrotra, a program manager at Maluuba, said figuring out how to win these types of videogames is actually quite complex, because of the huge variety of situations you can encounter while playing the game.

With reinforcement learning, an agent gets positive or negative responses for each action it tries, and learns through trial and error to maximize the positive responses, or rewards.

An AI-based system that uses supervised learning would learn how to come up with a proper response in a conversation by feeding it examples of good and bad responses. A reinforcement learning system, on the other hand, would be expected to learn appropriate responses from only high-level feedback, such as a person saying she enjoyed the conversation - a much more difficult task.

AI experts believe reinforcement learning could be used to create AI agents that can make more decisions on their own, allowing them to do more complex work and freeing up people for even more high-value work.



Previous
Next
Pioneer's Flagship Se-Monitor5 Hi-Res Headphones Released        All News        Nokia Unveils the World's Fastest Routers
Western Digital's SanDisk Subsidiaries Seek Injunctive Relief Against Toshiba in the Superior Court of California     General Computing News      Nokia Unveils the World's Fastest Routers

Get RSS feed Easy Print E-Mail this Message

Related News
Intel to Bring Silicon-Based Security to AI and Blockchain Workloads
Microsoft to Buy Bonsai to Build 'Brains' for Autonomous Systems
Microsoft Releases Microsoft News App For Windows 10, iOS and Android
Nvidia Uses AI to Produce High-quality, 240fps Slow-motion Video From 30fps Source
IBM's AI Machine Learns to Debate Humans
Google Uses Deep Learning to Predict When a Patient Will Die
Intel to Showcase AI and HPC Demos at ISC
Deep Mind's Neural Scene Rendering System Predicts 3D Surroundings Using Its Own Sensors
Microsoft Follows Amazon in Checkout-free Retail Technology: report
Samsung Launches Fund to Invest in AI Startups
E3 2018: Microsoft 'Halo Infinite' Trailer Unveiled, Ninja Theory, Undead Labs, Playground Games, Forza Horizon, and Gears of War 5
Microsoft Highlights Intelligent Cloud, Intelligent Edge vision at Computex Taipei

Most Popular News
 
Home | News | All News | Reviews | Articles | Guides | Download | Expert Area | Forum | Site Info
Site best viewed at 1024x768+ - CDRINFO.COM 1998-2018 - All rights reserved -
Privacy policy - Contact Us .