- For decades, AI advancements have been put to the test through games.
- But games also offer an effective training ground for AI to learn and improve.
- AI training through games like Gran Turismo, Minecraft, and StarCraft could lead to real-life applications, from autonomous driving to business management.
- We speak with AI expert Kenneth Stanley, inventor of the evolutionary genetic NEAT algorithm often used in training gaming AI.
- Elevate your gaming experience with a gaming VPN to minimize ping and lag.
Artificial intelligence once made headlines for beating the world’s best at chess and Checkers. Today, AI is being put to the challenge in video games like Gran Turismo and Starcraft.
But these games are not just a way of assessing just how intelligent the machines really are. Even more so, games offer valuable training to AI, allowing them to learn as they play. In this article, we’ll explore this dynamic and the potential real-world applications of AI advancements gained through gaming.
A brief history of AI in gaming
The evolution of AI in gaming traces its origins back to Alan Turing’s concept of the “imitation game” in the 1950s. Turing’s bold inquiry, “Can machines think?” set the stage for a transformative journey into the realm of AI and gaming.
In his thought experiment, Turing proposed a test that would forever shape the landscape of AI. Through the imitation game, a human judge would engage in text-based conversations with both a human participant and a machine. Should the judge be unable to consistently differentiate between the human and the machine responses, the machine would be deemed to have passed the test, achieving a level of conversational proficiency akin to human intelligence.
Turing’s visionary concept laid the foundation for exploring the intersection of human cognition and machine capabilities. It challenged conventional notions of intelligence and sparked the pursuit of creating machines that could emulate human thought processes.
Computer scientist Arthur Samuel coined the term “machine learning” in 1959. Samuel’s innovative fusion of artificial intelligence and gaming materialized in a Checkers-playing program. This program was unlike any before it. Samuel’s creation could learn from its mistakes, progressively refining its gameplay and strategy through experience.
The Checkers-playing program marked a watershed moment, illustrating the potential for machines not just to follow programmed instructions, but to adapt and improve autonomously—a fundamental shift that laid the groundwork for the evolution of AI in gaming.
And the milestones in AI gaming didn’t end there. In 1997, IBM’s Deep Blue confronted humanity’s reigning chess champion, Garry Kasparov, in a historic six-game match. The outcome—Deep Blue’s victory—reshaped perceptions of AI’s capabilities. The program’s strategic prowess and ability to outwit a human grandmaster heralded a new era where machines could rival human intellect in the realm of strategy and tactics.
These early chapters of AI in gaming sowed the seeds for further advancements, setting the stage for the astonishing feats to come. From AlphaGo’s triumph in the complex game of Go to the creation of formidable virtual adversaries in modern video games, AI’s evolution continues to captivate and redefine the gaming landscape, pushing the boundaries of human-machine interaction and paving the way for a future where gaming and artificial intelligence are inextricably intertwined.
Games as the perfect AI playground
Prominent AI labs, including those at Sony, Google, and Microsoft, have developed techniques that enable computer programs to conquer intricate board games and immersive video games with unprecedented mastery.
Kenneth Stanley, the former team leader of OpenAI’s Open-Endedness Team (which helps develop self-learning AI that can adapt to new tasks and environments), introduced the NeuroEvolution of Augmenting Topologies (NEAT), a genetic algorithm, which means it’s inspired by mutations and crossovers found in biological evolution. Developers have been applying the algorithm to real-time calculations in video games like the educational NERO and iconic titles such as Mario Bros. and the Monopoly board game. NEAT’s dynamic neural network adapts to player actions while the game is running.
For Stanley, games present an ideal testing ground for algorithms like NEAT. “Unlike costly robotic hardware, games require fewer resources and allow for rapid AI experimentation without real-world risks,” he explains in an exclusive interview with ExpressVPN.
But games have served not only as tests for AI but also as valuable training grounds. “In some cases, the motivation is making the game better, but in most cases, it’s about making the AI better,” says Stanley. “Games act as a vehicle for enhancing AI capabilities.”
“Sometimes the motivation for incorporating AI is to make the game better, but in most cases, it’s about making the AI better. Games act as a vehicle for enhancing AI capabilities.”
While driving simulators aren’t geared for AI, Stanley notes, games like Gran Turismo can be played by AI—and fact training using Gran Turismo led to the creation of GT Sophy, an AI with potential applications in self-driving cars. “Another good example of an AI sandbox is Minecraft with its limitless possibilities,” he says. “It allows for an approximation to real-life scenarios. Games are the most sophisticated kind of simulator.”
The unique combination of a constrained, controlled environment and free creative space in games makes them great for trying out AI methods. This helps advance AI and offers useful insights for solving real-world problems.
Examples of AI learning through video games and their broader applications
You might think you get a lot out of gaming (entertainment, excitement), but AI that play games have the potential to gain a lot more—intelligence that can be extended to other applications. Here are a few examples of how that is being done:
- GT Sophy, Sony’s AI racing driver featured in Gran Turismo, is trained via reinforcement learning, racing virtual cars for countless hours. This hints at future applications in self-driving cars and drones.
- Microsoft researchers are testing an AI that allows users to build their worlds in Minecraft using simple prompts rather than hours of manual clicks. This could aid those challenged by traditional gaming controls and lead to broader accessibility solutions.
- AI playing the classic Q*bert game discovered and exploited a previously unknown bug that allowed it to rack up unlimited points. The AI was simply trying to find the best solution and inadvertently revealed the bug. It bodes well for evolutionary algorithms, which the AI was based on, in which AI are tweaked slightly to find a version that performs best.
- Teaching AI to conquer StarCraft, a complex multiplayer strategy game, means training it to gain management skills. The game’s challenges mirror real tasks—decision-making, strategizing, and resource management. A victorious AI would show algorithms can master real-life tasks.
- A researcher from the University of Cambridge created an AI agent that can control characters in the battle simulator Pokemon Showdown, in which teams of six Pokemon compete against others. The AI analyzes the teams based on the characters’ strengths and weaknesses, predicting the outcomes. This could inspire technologies capable of managing teams in uncertain environments such as war zones.
Why humans can still beat AI at games
Despite advancements in AI, there remain games where human expertise prevails. Games such as Settlers of Catan, Dungeons & Dragons (D&D), and Cards Against Humanity stand as prime examples of challenges that AI struggles with. Even in games like Gran Turismo, Pokémon, and Monopoly, human players can still outshine their AI counterparts.
“AI will likely eventually master all conventional games. But first, we should ask ourselves what we define as a game,” asserts Stanley. “When games approach real-life complexity—such as designing machines or building a rocket—an AI would get in trouble. If it involves real creativity and too many degrees of freedom, it becomes challenging for AI to outperform human players. But in the long, long run, we can’t even be sure of that.”
This uncertainty emerges as researchers pursue the development of Artificial General Intelligence (AGI)—AI that is able to perform any task as well as a human can—to bridge this gap. But the training methods remain a question mark. “At the moment, we don’t know how to teach AI to be truly creative and come up with something new no one thought of before. It does happen in the small constrained worlds of gaming, but the real world isn’t small and constrained,” Stanley explains. “AI lacks instinct, but to teach it that, we need to know first what instinct entails.”
“At the moment, we don’t know how to teach AI to be truly creative and come up with something new no one thought of before. AI lacks instinct, but to teach it that, we need to know first what instinct entails.”
AI’s current limitations stem from data availability and its capacity to tackle intricate, open-ended tasks. Stanley clarifies that amassing the voluminous data essential for AI training, coupled with constructing networks capable of assimilating this data, presents a formidable challenge. Furthermore, AI’s reliance on textual information and its struggle with non-verbal or ineffable aspects further complicate matters. Existing AI models also struggle to understand chronology, a key element in comprehending novelty and intricate processes.
A solution might be lurking within the gaming realm once again. Researchers posit that Dungeons & Dragons, a game known for its collaborative storytelling nature, could serve as an incubator for AGI. Beth Singler, a digital anthropologist at the University of Zurich, introduced the “Elf Ranger Test” as an alternative to the Turing Test. This test suggests that if AI can adeptly engage in D&D, it might be edging closer to achieving AGI status.
The future of AI in gaming and beyond
Looking ahead, AI’s role in gaming is set to expand even further. One clear trend is the use of narrative, social, and educational AI to make gaming more immersive and realistic. Fortnite, for example, introduced bots to train new players and a matchmaking system to connect players with similar skills. AI strides made in games like Starcraft II and Dota 2 are making games more customizable, helping them adapt in real-time to suit individual players’ skills, preferences, and tactics.
“To embrace AI without fear, view it as a tool for amplifying human abilities.”
Beyond the world of gaming, AI holds the potential to contribute to solving intricate global predicaments like climate change and healthcare advancement. However, this promise is coupled with concerns about AI attaining emotions and cognition.
Amid these advancements, concerns linger about the possible dark outcomes of using AI. “Concerns range from practical problems like disinformation or people losing their jobs to Terminator-like scenarios like the end of civilization. No matter how unlikely, however, you still want to make sure there’s zero probability”, says Stanley. “Ultimately, everything is creativity. If we cross that barrier, the world would not look the same, and it’s hard to fathom what that world would be like. What we do know, is that the real source of human pleasure isn’t consumption. The joy of being human lies in self-expression and creativity. So how can we protect that?”
Addressing these concerns is pivotal to shaping a balanced future. Stanley advocates for embracing AI’s growth instead of retreating from it.“To embrace AI without fear, view it as a tool for amplifying human abilities,” he says.
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FAQ: About AI Gaming
Is there an AI Dungeons & Dragons game?
Yes, there is an AI Dungeons and Dragons game called AI Dungeon. It is a text-based adventure game where you can interact with the GPT-3 language model to create your own D&D stories. You can choose your character, race, class, and background, and then you can explore a randomly generated world, fight monsters, and complete quests. The AI Dungeon master will help you along the way, and it will even generate dialogue for your characters.
While AI Dungeon offers a creative and freeform experience akin to Dungeons & Dragons, it’s important to note that it’s not a complete replacement for D&D due to occasional challenges in generating coherent and realistic storylines. The game is available on the web, Steam, iOS, and Android devices, with both free and premium versions offering extra features.
Here are some other AI-powered D&D games:
- Dungeon Alchemist is a web-based game that allows you to create your own D&D dungeons. You can use the AI to generate maps, monsters, and treasure.
- Dungeon Master’s Assistant is a software program that helps you run D&D games. It can generate random encounters, track initiative, and manage your character sheets.
- Dungeon Scrawl is a web-based tool that allows you to create your own D&D maps. You can use the AI to generate terrain, objects, and characters.
Are there any games about AI?
Certainly, there are numerous games that delve into the realm of artificial intelligence. Some prominent examples of AI games include:
- Halo 4: A first-person shooter with the Master Chief combating the corrupted AI Cortana
- Cyberpunk 2077: A role-playing game set in a dystopian future where AI is commonplace
- SOMA: A horror game where you explore an underwater facility that is inhabited by AI who are trying to survive
- Detroit: Become Human: A narrative adventure wherein androids grapple with choosing obedience to humans or fighting for autonomy
- Portal 2: A puzzle game where players utilize the intellect of the AI GLaDOS to solve intricate challenges
- The Talos Principle: A puzzle game that explores the nature of consciousness and AI
- Horizon Zero Dawn: An action-adventure game unfolding in a post-apocalyptic world featuring human-AI coexistence, questioning sentience in machines
- System Shock: A survival horror game where you must fight your way through a space station that has been overrun by AI
- NieR: Automata: An action RPG portraying androids battling machines, delving into questions about consciousness and existence
- Mass Effect Series: A sci-fi RPG where players confront the AI Reapers, intent on eradicating organic life
- Metal Gear Solid Series: A stealth action franchise with Solid Snake opposing the AI-controlled Patriots’ global dominance aims
These are just a glimpse of the many AI-themed games. As AI technology evolves, we can anticipate more titles delving into this intricate and captivating subject.
Has AI gone too far?
Whether AI has gone too far is a complex question with no easy answer. There are many different opinions on this issue, and it is likely to continue to be debated for many years to come.
Some contend that AI has already exceeded boundaries, with machines potentially outstripping human intelligence, stoking fears of subjugation or destructive applications.
Others believe that AI is still in its early stages of development, and that we have nothing to worry about. They argue that AI is simply a tool, and that it is up to us to decide how we use it. They believe that AI can be used for good, such as solving complex problems and improving our lives.
Ultimately, the question of whether AI has gone too far is a matter of opinion. The discourse encapsulates a spectrum of potential hazards and advantages associated with AI:
Risks:
- Creation of autonomous weapons capable of independent lethal actions.
- Potential for AI-driven manipulation and misinformation.
- Escalating unemployment as machines supplant human labor in various sectors.
- Prospect of AI surpassing human intellect, raising concerns over loss of control.
Benefits:
- Potential for addressing intricate challenges like climate change and diseases.
- Enhancing life quality through task automation, personalized healthcare, and novel entertainment.
- Facilitating deeper self-awareness and comprehension of the world.
It is important to consider both the potential risks and benefits of AI carefully before deciding the extent to which we’ll implement it. There is a need for ethical guidelines for the development and use of AI.
Should AI have rights?
The question of whether AI should have rights is complex and has been discussed by experts for a long time. Some argue that AI shouldn’t have rights as they’re not like living beings, just programmed machines. Others believe AI should have some limited rights to protect them from harm and exploitation. People in favor of AI rights think they might become like sentient beings with feelings, while those against worry about unintended consequences and the challenge of defining AI consciousness.
There are many factors to consider, such as the level of intelligence and autonomy that AI systems will eventually achieve, the potential benefits and risks of granting them rights, and the ethical implications of doing so.
How can I make an AI that plays games?
There are various methods to make an AI that plays games. The best approach depends on the specific game and the desired level of performance. Here are a few:
- Reinforcement learning: A type of machine learning where the AI learns by trial and error. The AI is given a reward for taking actions that lead to a desired outcome, and a penalty for taking actions that lead to an undesired outcome. Over time, the AI learns to take actions that maximize the reward.
- Rule-based AI: A type of AI that is programmed with a set of rules that define how to play the game. This approach is relatively simple to implement, but it can be difficult to create rules that cover all possible situations in the game.
- Monte Carlo tree search: A type of AI that uses a tree search algorithm to explore the game state space. This approach is more complex than rule-based AI, but it can be more effective in games with a large state space.
- Evolutionary algorithms: A type of AI that uses a process of mutation and selection to evolve a population of AIs. This approach can be used to create AIs that are good at playing games that are difficult to define with rules or that have a large state space.
Can AI make games?
Yes, here are ways AI can be used to make games:
- Generating game content: AI can be used to generate game content, such as levels, characters, and dialogue. This can be done using techniques such as machine learning and natural language processing. For example, the AI game engine Dreaming can generate levels, characters, and dialogue, and it can also design game mechanics.
- Designing game mechanics: AI can be used to design game mechanics, such as how players interact with the game world and how the game progresses. This can be done using techniques such as reinforcement learning and evolutionary algorithms. For example, the game Gauntlet uses AI to personalize the game experience by tracking the player’s progress and preferences, and it uses this information to generate challenges that are tailored to the player.
- Testing games: AI can be used to test games, such as by playing the game and looking for bugs or imbalances. This can be done using techniques such as machine learning and computer vision. For example, AI can be used to play games and look for patterns that indicate bugs or imbalances.
- Personalizing games: AI can be used to personalize games, such as by tailoring the game experience to the individual player’s preferences. This can be done using techniques such as machine learning and natural language processing. For example, the text-based adventure game AI Dungeon uses AI to generate the story, and the AI can generate different endings to the story, depending on the player’s choices.
