Cognizant of this, the team built Suphx to tackle 4-player Japanese Mahjong (Riichi Mahjong), which has one of the largest Mahjong communities in the world. Three top investment pros open up about what it takes to get your video game funded.įor these reasons, it’s hard for a Mahjong player - let alone a machine learning model - to decide which moves to make based on private tiles alone. Taking into account the up to 13 game tiles in each person’s hand, the 14 tiles in the “dead” wall visible throughout the game, and the 70 tiles in the “live” wall that becomes visible once the tiles are drawn and discarded, on average there are more than 10 48 hidden states, indistinguishable to players, at any one time. Plus, Mahjong has a huge number of possible winning hands, and different winning hands result in different winning scores for each round. The loss of one round doesn’t mean a player played poorly they might tactically lose to ensure they secure the top rank. The paper’s coauthors note that Mahjong is an imperfect information game with complicated scoring rules. “We believe our techniques designed in Suphx for Mahjong, including global reward prediction, oracle guiding, and … policy adaptation have great potential to benefit for a wide range of real-world applications.” Tackling Mahjong

“Most real-world problems such as finance market predication and logistic optimization share the same characteristics with Mahjong - i.e., complex operation/reward rules, imperfect information,” wrote the paper’s coauthors.

Moreover, its researchers assert that the learnings are applicable to other domains, like the enterprise, where mundane but cognitively demanding tasks impact workers’ productivity. Games are an analog of the real world, with a measurable objective, and they can be played an infinite amount of times across hundreds (or thousands) of powerful machines.

A revised preprint paper out this week delves a bit deeper, revealing that Suphx - whose performance improved with additional training - is now rated above 99.99% of all ranked human players on Tenhou, a Japan-based global online Mahjong competition platform with over 350,000 members.īuilding superhuman programs for games is a longstanding goal of the AI research community - and not without good reason. Last August, Microsoft Research Asia detailed an AI system dubbed Super Phoenix ( Suphx for short) that could defeat Mahjong players after learning from only 5,000 matches. Join gaming leaders, alongside GamesBeat and Facebook Gaming, for their 2nd Annual GamesBeat & Facebook Gaming Summit | GamesBeat: Into the Metaverse 2 this upcoming January 25-27, 2022.

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