MIT researchers have developed a bot equipped with artificial intelligence that can beat human players in tricky online multiplayer games where player roles and motives are kept secret. Many gaming bots have been built to keep up with human players. Earlier this year, a team from Carnegie Mellon University developed the world's first bot that can beat professionals in multiplayer poker. DeepMind's AlphaGo made headlines in 2016 for besting a professional Go player. Several bots have also been built to beat professional chess players or join forces in cooperative games such as online capture the flag.
Programmers at OpenAI, an artificial intelligence research company, recently taught a gaggle of intelligent artificial agents -- bots -- to play hide-and-seek. Not because they cared who won: The goal was to observe how competition between hiders and seekers would drive the bots to find and use digital tools. The idea is familiar to anyone who's ever played the game in real life; it's a kind of scaled-down arms race. When your opponent adopts a strategy that works, you have to abandon what you were doing before and find a new, better plan. It's the rule that governs games from chess to StarCraft II; it's also an adaptation that seems likely to confer an evolutionary advantage.
If you've ever been to an expensive restaurant and ordered a familiar dish like, say, lasagna, but received a plate with five different elements arranged in a way that does not at all resemble what you know as lasagna, then you have probably tasted deconstructionism. This approach to cuisine aims to challenge the way our brain makes associations, to break existing patterns of interpretation and, in so doing, to release unrealized potential. If the different elements work together harmoniously, it should be the best lasagna you've ever tasted. In principle, the 5th Generation network is deconstructed. Firstly, with its Service-Based Architecture (SBA) the core of the network is a mesh of interconnected services, each working independently but collaboratively.
As most people know at this point, connecting our brains to machines is no longer theoretical science fiction. In fact, it could be transforming how we communicate as a species. AI-powered brain-interface technologies could make people smarter by helping them make better decisions, improve working memory, and process more information more efficiently. An AI-infused brain would truly revolutionize how, and how quickly, we learn by making it possible to upload knowledge of a number of domains directly to our brains, including in high- skill fields such as engineering, law, medicine, and science. But what happens when everyone is equally as smart as everyone else?
Europilot is an open source project that leverages the popular Euro Truck Simulator(ETS2) to develop self-driving algorithms. A convolutional neural network (CNN) controls the steering wheel inside ETS2. Think of europilot as a bridge between the game environment, and your favorite deep-learning framework, such as Keras or Tensorflow. With europilot, you can capture the game screen input, and programmatically control the truck inside the simulator. Europilot can be used in one of two ways: training or testing.
Researchers at Carnegie Mellon University have demonstrated that people who play a game with a robot suffer in performance when the robot criticizes them. Trash talking has a long and colorful history of flustering game opponents, and now researchers at Carnegie Mellon University have demonstrated that discouraging words can be perturbing even when uttered by a robot. The trash talk in the study was decidedly mild, with utterances such as "I have to say you are a terrible player," and "Over the course of the game your playing has become confused." Even so, people who played a game with the robot ― a commercially available humanoid robot known as Pepper ― performed worse when the robot discouraged them and better when the robot encouraged them. "This is one of the first studies of human-robot interaction in an environment where they are not cooperating."
Artificial intelligence is the future. Artificial intelligence is science fiction. And it is already part of our everyday lives. All these three statements are true, it all depends on what flavor of AI you are referring to. For instance, when Google DeepMind's AlphaGo program defeated the South Korean Master, Lee Se-dol in the board game "Go" earlier in 2016, the terms AI, machine learning and deep learning were used in the media to describe how DeepMind won.
"Death Stranding" earned the most nominations in the Game Awards, which will be given out Dec. 12 in Los Angeles. The new game from famed designer Hideo Kojima ("Metal Gear Solid") collected nine nominations, including Game of the Year, Best Action/Adventure Game, Best Game Direction, Best Art Direction and Best Score. Actors Norman Reedus and Mads Mikkelsen, who portray Sam Porter Bridges and Cliff, respectively, in the PlayStation 4 game, earned nominations for Best Performance. They were joined by Ashly Burch as Parvati Holcomb in "The Outer Worlds," Courtney Hope as Jesse Faden in "Control," Laura Bailey as Kait Diaz in "Gears 5" and Matthew Porretta as Dr. Casper Darling in "Control." Considered the Oscars of the video game industry, the Game Awards began in 2014, established by longtime video game journalist Geoff Keighley.
In January, artificial intelligence(AI) powerhouse DeepMind announced it had achieved a major milestone in its journey towards building AI systems that resemble human cognition. AlphaStar was a DeepMind agent designed using reinforcement learning that was able to beat two professional players at a game of StarCraft II, one of the most complex real-time strategy games of all time. During the last few months, DeepMind continued evolving AlphaStar to the point that the AI agent is now able to play a full game of StarCraft II at a Grandmaster level outranking 99.8% of human players. The results were recently published in Nature and they show some of the most advanced self-learning techniques used in modern AI systems. DeepMind's milestone is better explained by illustrating the trajectory from the first version of AlphaStar to the current one as well as some of the key challenges of StarCraft II.
The trash talk in the study was decidedly mild, with utterances such as "I have to say you are a terrible player," and "Over the course of the game your playing has become confused." Even so, people who played a game with the robot -- a commercially available humanoid robot known as Pepper -- performed worse when the robot discouraged them and better when the robot encouraged them. Lead author Aaron M. Roth said some of the 40 study participants were technically sophisticated and fully understood that a machine was the source of their discomfort. "One participant said, 'I don't like what the robot is saying, but that's the way it was programmed so I can't blame it,'" said Roth, who conducted the study while he was a master's student in the CMU Robotics Institute. But the researchers found that, overall, human performance ebbed regardless of technical sophistication.