After Dominating Chess, A Machine Learning AI Is About To Beat Physics-Based Sports Games Too

After Dominating Chess, A Machine Learning AI Is About To Beat Physics-Based Sports Games Too

Artificial intelligence has already beaten chess. Hell, the most sophisticated AI systems have a very good chance against top players in the incredibly complicated game of Go.

But, in the uber-complicated car-based soccer game of Rocket League, can an AI do a boosted 360 aerial bicycle kick power shot from the midline? Can it pinch a ball off the side ramp so precisely it sails into the goal at 145 km/h? No, at least not yet, but AI can apparently dribble like a madman. It can fake out legitimately skilled players and score goals by flicking the ball off the hood and into the net.

For more than a week, players have been driven up the wall (sometimes literally, in game) by machine learning-based AI that’s been hacked into games of Rocket League. One video posted on the r/RocketLeague subreddit last week claimed a bot was being used in a ranked game employing freakishly impressive ball handling skills. And that’s just one example of many being posted by the RL community.

The game is close to 8 years old, but the frenetic, high flying, high speed car soccer game is still enjoyed by close to 90,000 players across most platforms, according to

The AI is called Nexto, and was originally developed by members of the Rocket League community as a kind of training tool. But as videos of the bot online show, the capabilities of machine learning AI have gotten so advanced they can actively dunk on real-life players in an incredibly complicated, physics-based environment. Rocket League streamer MrCupid posted video of him getting matched with the Nexto bot twice in one day.

Rocket League is already an incredibly complicated game. From the outset, it uses strange physics that make it hard for a beginning player to comprehend. The ball is oversized compared to the car, and the player’s car will interact with the ball differently depending on the shape of the vehicle and which part of the car is touching it. This all makes “dribbling,” or the act of keeping the ball on top of the car while manoeuvring around other players, one of the hardest skills to learn in Rocket League.

Wired reported Thursday that Reed Wilen, a top player in Rocket League who goes by “Chicago” online, told Wired that during a random game online, he encountered a player who was moving in an erratic way, but when the opponent took control of the ball it managed to manoeuvre it perfectly on the hood of its car.

The thing is, the bot wasn’t meant to be taken out into free play. It was designed by a team of software engineers and other computer scientists in their spare time and was released on RLGym, an API and open-source library for Rocket League bots. Those AI are then ported to other systems like RLBot made to help players get in some high-skill training and for developers to flex their skills. Nexto, and other bots, have been trained on hours upon hours of gaming in Rocket League, where it eventually learns the correct inputs needed to put the ball in the goal.

This kind of machine learning operates on a kind of engineering reward function. Essentially, the AI is given a goal, and it iterates on that problem a multitude of times until it achieves the desired function. Other functions of the AI can be hardcoded, but all the trickshots and perfect dribbling are all machine learning-based.

In a Reddit AMA earlier this month, one of the RLGym authors who go by Aech online confirmed the bot was brought into an online environment using third-party tools. The bot maker also said that, outside its training environment, Nexto won’t learn any new moves. Rolv, one of the members who developed Nexto, told Wired there are even more advanced versions of Nexto on the plate, but those are still unreleased publicly. One will supposedly even get better as it watches human gameplay.

“[Nexto] took an enormous engineering effort and a lot of community support to do, and it is not easily replicable,” Aech wrote. “Constructing a learning algorithm and environment that can lead to a bot as good as Nexto requires intimate knowledge of distributed computing, reinforcement learning, a solid intuition about why good rocket league players are good, and the ability to accurately predict how a change in the environment will lead to a desired change in the agent.”

Nexto has become a source of interest for months in the Rocket League community, with some players adding features to make it enact some player-like behaviours including trash talk. Players have even joked how Nexto seems to reinforce the infamous “Rule 1” that says if two players end up bumper to bumper, they remain that way until an external force breaks them up.

Players are certainly worried about encountering the bot in their games. The developer, Psyonix — owned by the massive publisher Epic — told PCGamer earlier this month that they’re “investigating solutions.”


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