5 Game Development Companies Integrating AI Research

We frequently use metrics to demonstrate how far Artificial Intelligence (AI) has progressed. We build on prior work, and if we've done our job effectively, we'll be able to take a little stride forward in the future. What actually shifts our perspective is recognizing what our actions allow us to achieve.

 

AI isn't a new concept in computer games. For years, game creators have used the technology to alter the behavior and decision-making of non-player characters (NPC). Today's computers and video games provide a huge test platform for AI research and development.

 

( Also Read - Types of AI )

 

Machine learning has advanced significantly in past years, with artificial agents achieving superhuman efficiency in challenging domains such as Go, Atari, and various poker variations. These game domains, like their predecessors’ chess, checkers, and backgammon, have sparked study by presenting artificial intelligence developers with complicated yet well-defined problems.

 

11th of May, 1997. The world waits in anticipation as the IBM supercomputer Deep Blue, which was built to be the world's finest chess player, eventually defeats world chess champion, Garry Kasparov, in a match. It's never happened before. The news quickly circulated throughout the internet. A guy is defeated by the machine. (source)

 

Building AI gamers that can beat human players is more than a fun project. The goal is to use those programs to tackle real-world challenges, says Sebastian Risi. He is an AI researcher at the IT University of Copenhagen in Denmark. AIs created to play the online game Dota2 taught a robotic hand how to grasp items, for example.

 

The findings were published in January by California researchers at the San Francisco–based startup OpenAI. AlphaStar's inventors believe its AI can assist scientists with difficult jobs. AIs might, for example, aid with the simulation of climate change or the comprehension of speech.

 

( Also Read -  Best Programming Language for Game Development ) 

 

What is it about board games and computer games that pique the interest of artificial intelligence researchers? It all began with checker-playing algorithms in the 1950s when academics were astounded by the "thinking" that the algorithms displayed. Then came chess, which remained a focus topic of AI research far into the 2000s. 

 

Fast forward to 2015, when a viral video of a neural network playing Super Mario sparked widespread interest in video game AI, moving far beyond the realm of video game creators and into the realm of conventional data science.

 

This obsession with gaming and artificial intelligence research is difficult to ignore, and I believe there is a need to investigate why. According to Towards Data Science, There are three major benefits of games in AI research that we shall discuss:

 

• Games are a self-contained issue in which all possible events, variables, and outcomes are known in advance.

 

• In games, data may be created through randomized gameplay.

 

• Because of the predetermined and regulated surroundings, games can have deterministic results.

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Application of AI and ML in Game Development

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Game Development Companies that make use of AI research

 

There comes a point where it feels like we're developing AI for the purpose of building AI versus games, which is good and is the privilege of research. However, it's puzzling when the developers of these algorithms claim that these algorithms have enormous potential for solving real-world issues at an incredible AGI level while being trapped in a cycle of identifying the next game to automate rather than addressing an actual industrial issue.

 

( Suggested Reading - Game Theory in AI )

 

Smaller teams would be able to create far larger and more complicated games as a consequence of such technologies. Larger studios may also be able to push the boundaries when it comes to developing open-world settings and simulations and systems that approach the complexity of the actual world. “ On the one hand, it will be a lot easier to create games.

 

The following AI game developing companies are employing cutting-edge AI technology to improve the gaming experience, whether they're using behavior trees to affect non-player characters or building AI algorithms to beat humans in their own games.

 

1. EA

 

Electronic Arts (EA) is a digitally active entertainment firm that creates and distributes gaming content and web services to a global audience of over 300 million gamers.

 

EA is recognized for its tremendous portfolio of gaming titles, including Madden NFL, EA Sports, Need for Speed, Battlefield, and The Sims, but it is also renowned for its constant innovation. For example, a team at Electronic Arts recently created an AI bot that trained itself how to play Battlefield 1. Isn’t it Fascinating?

 

EA created a 3D gaming world particularly for deep learning networks to navigate, in addition to the self-teaching Battlefield 1 agent. 

 

 

2. TruSoft

 

TruSoft is a software firm that conducts research and creates artificial intelligence technology. Artificial Contender (AC), the highlighted technology, is an AI software capable of delivering behavior patterns of game operatives.

 

Agents with a more natural development style are created using AI technology. Agents can be educated through controls to understand human actions and gaming techniques, rather than merely being programmed. AC, which is already in use in video games, allows actual celebrities and sportsmen to train their game-version of themselves.
 

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Some games which are applying AI

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3. APEX Game Tools

 

Apex Gaming Tools, founded in 2014, develops artificial intelligence solutions and tools for a range of game genres. Apex does its own research in machine learning, algorithms, and cybernetics in addition to collaborating with other research organizations and universities to improve AI.

 

Utility AI, a scoring-based framework for computer games, is one of Apex's numerous products. Utility AI makes many decisions, rates each possible option, and then takes action. Apex technologies are used by thousands of developers and businesses to power their games. In shooting games, Apex Utility AI can be used to determine whether it should reload weaponry, shoot, seek shelter, or assault.

 

( Further Read - Applications of IoT in Gaming Industry )

 

4. Blizzard Entertainment

 

World of Warcraft, StarCraft, and Diablo are just a few of the notable games developed by Blizzard Entertainment.

 

StarCraft is a strategy game featuring single-player and multiplayer features developed by the firm. Researchers are particularly interested in the game because of its real-time strategic role in testing and assessing artificial intelligence.

While AI products such as AlphaGo have tackled tasks such as the board game Go, Blizzard's StarCraft introduces new difficulties and an environment in which AI cannot view the full space as it can in a board game.

 

Blizzard has launched a set of tools called SC2LE in collaboration with Deep Mind that will accelerate Blizzard's strategic game, StarCraft II, as a platform for AI research. DeepMind has made significant advances to protein folding via AlphaFold and has lately received attention for its efforts. Other projects have also found applications in the industry. So DeepMind has done more than just replace gamers at a high cost.

 

5. Opsive 

 

Opsive is an independent studio that uses the Unity programming engine to produce games and assets.

 

The Behavior Designer product from Opsive is an AI solution for the Unity engine that generates behavior trees. Game creators may use the behavior tree tool to construct agents that switch between different sets of duties, resulting in non-player character behaviors.

Multiple games, including A Dragon Named Coal, Creativerse, Immortal Redneck, and Warcube, are presently using Opsive's Behavior Designer.

 

Refer to this pdf from Springer for More about Games and AI.

 

 

Conclusion

 

Given the present state of affairs, we can only expect a slew of new studies to focus on real-time gaming. Learning what can be done is one of the most difficult aspects of AI. We will see a rise in attempts to develop bots that can do well in such games now that we know artificial agents can behave in real-time. We've taken the first step toward the next great thing. Nobody knows how long it will take, but one thing is certain: we will succeed.