Gaming and Esports are growing rapidly. Technologies like artificial intelligence (AI) are some of the factors that drive this growth. AI in gaming is making an impact in the following ways:
1. Coaching apps for Esports
Esports isn’t just about playing games. It involves big money. Players can earn a high salary, and they can get lucrative sponsorship deals. Big brands like Red Bull, Comcast, Intel, Honda, Pepsi, Coca-Cola, The Kraft Group, and Mercedes Benz sponsor Esports.
Esports players face a highly competitive environment. They need to improve their overall playing skills, and they just can’t get enough practice.
AI-powered coaching apps can help Esports players. These apps can suggest better strategies to players, and they coach players to improve their performance.
SenpAI is an example. This AI-powered desktop and web app can help players to improve their performance in popular games like League of Legends and Valorant. The app provides in-depth stats for players to analyze. SenpAI also offers in-game guidance.
2. Identifying negative player behavior
Esports players come from all kinds of backgrounds. Most of them are courteous, professional, and positive-minder people. However, some Esports players have an unfavorable emotional state.
Many Esports leagues and tournaments have a high difficulty level. Such a game requires players to focus well. Negative player behavior can affect other players in all games, and the impact is more in difficult games.
There are persistent demands in the game world to eliminate and control negative emotional outbursts and bullying. Many games allow players to report negative behavior. However, the lack of manpower makes it hard to act on those reports.
AI can help. AI techniques like machine learning and natural language process can identify negative player behavior and players with an aggressive emotional state.
GGWP is one such AI system. It helps to detect abusive behavior among gamers. GGWP also automatically responds to reports and incidents, which makes game moderation easier.
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3. Making virtual reality (VR) games more engaging with the help of artificial intelligence
AI can make VR games more engaging. AI researchers at the University of Bath in the UK are making characters in VR games more interesting. They have made the movements of these characters more realistic using AI.
This team of researchers has worked with Ninja Theory, a UK-based game studio. Together, they are implementing an AI project named AI Touche to create more engaging virtual worlds.
Several AI capabilities like machine learning and computer vision can be used to make VR games more exciting. AI and analytics can also provide better insights for VR games.
4. Transforming Esports betting with AI technology
As Esports grows, we see significant growth in Esports betting. Betting is tough everywhere. That holds good for Esports too. However, Esports betting is different from other bettings in one aspect.
Esports is data-intensive by its very design. After all, Esports are computer games. Other sports don’t produce the volume of data generated by Esports. You can get massive data sets from Esports. These could include team ranking, player ranking, tournament statistics, game statistics, etc.
AI and data science can work together to derive high-quality insight from these data sets. You can use these insights to create better betting odds. This can make Esports betting much more data-driven than other bettings.
Esports Technologies, a well-known company in the Esports landscape has filed a patent application concerning Esports betting. The company has created an AI-powered “Real-Time Odds Modeling & Simulation System” for Esports betting.
5. Improving the gaming experience with game AI
In the world of video games, most games involve human players interacting with a digital entity in the game. These digital entities are also called “non-player characters” (NPCs). Much of the game design and game programming involves making these interactions exciting.
Developers of modern games incorporate AI agents while designing NPCs. This provides the NPCs the ability to learn from players’ actions. These AI systems can then bring twists to the gameplay scenarios.
Take the example of “enemy AI”, an AI technique used in many modern games. It uses a concept called the “Finite State Machine” to make highly competitive NPCs.
Human players need to try hard to defeat these NPCs, which makes games more engaging. Assassin’s Creed Rogue, Middle Earth Shadow of War, and Metal Gear Solid: The Phantom Pain are a few popular open-world games that use enemy AI.
6. Improving the performance of human players with the help of AI opponents
We talked about using AI systems for coaching Esports players, however, AI can also help players improve their skills in other ways. We already know how game developers can create hard-to-defeat NPCs. These AI-powered NPCs can be used as AI opponents to give challenging practice sessions to Esports players.
Take the example of OpenAI Five. This Esports team consists of 5 neural networks. These AI opponents can learn from the actions of human players. They can act intelligently, and human players can find it tough to beat them. These challenging practice sessions can help Esports players to improve their performance.
7. Improving transparency for sponsors in the games industry
Despite the media attention around it, Esports is still relatively new. Esports has considerable growth potential. It needs resources for that growth, and sponsorships are important. Esports players, game developers, team managers, etc. are keen on getting large sponsorship deals.
Companies that sponsor Esports naturally have a different perspective. They want to increase their sales, and they need to capture the mind space of consumers. Their Esports sponsorship strategies must align with this fundamentally important objective. Naturally, these companies will sponsor players/teams keeping this objective in mind.
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Esports teams and players must create a credible story around their potential. Companies must find the right teams and players to sponsor. That can be hard, however, AI can help.
An AI system can help Esports teams and players find the right sponsor. Sponsors can find the right Esports teams and players to sponsor, thanks to AI systems. AI systems can extract relevant insights from massive Esports datasets for this.
FanAI is an example. The company offers transparency to sponsors, teams, and players. Its platform extracts meaningful insights from vast data sets for this. Sponsors can choose the right teams and players, thanks to this transparency.
8. Judging a player’s ability better with the help of AI
Many new Esports teams are coming up due to the rising popularity of Esports. New players are also entering this field. However, it takes many years to take gaming skills to great heights.
New teams can’t find highly experienced players easily. They employ scouting teams to spot new Esports talents. By its very nature, scouting for talents is a time-consuming job. It takes even longer for Esports due to its novelty.
Scouting teams need data to objectively evaluate a player’s performance. There’s plenty of data available on Esports. However, this data is scattered all over the place. That makes it hard to get meaningful insights from it.
An AI-powered system can help scouting teams judge the performance of players effectively. AI capabilities like image recognition can analyze videos. Machine learning can analyze vast data sets and provide insights to scouting teams.
Rival.ai is one such system. It uses various AI capabilities to analyze the performance of Esports players. Rival.ai can provide reports for scouting teams. Betting companies can use the Rival.ai reports too.
9. Improving Esports broadcasting with AI and ML (machine learning)
Esports broadcasters want to create that perfect program for their viewers. That requires significant experience. Esports is new, therefore, broadcasters can’t possibly have a lot of experience in this field.
Broadcasters will need to utilize their experience from other sports. They can’t solely depend on this strategy since Esports is different from other sports. Esports broadcasters need to understand the needs of consumers.
AI can help them, and an example is the IBM Watson Advertising Accelerator. This platform uses AI to predict the creative works that will drive the most consumer engagement. It will optimize the decision-making process based on the outcome of past broadcasting programs.
10. Making strategy games more engaging with AI
Turn-based strategy games like chess and poker are very interesting. Many such games have kept human beings enthralled for decades and centuries. A game of chess offers great satisfaction due to the turns and twists, furthermore, strategy-making keeps us thoroughly engaged.
The quality of the opponent significantly determines how interesting a strategy game session will be. A tough opponent will make you think really hard, however, an inexperienced opponent will make the game less interesting.
What if you can get an opponent that becomes better with every game? Your sessions with that opponent will become very interesting. AI can deliver that opponent. AI-powered “opponents” learn with every game that they play. They continuously optimize their strategies and performance.
An example is Libratus from Microsoft that defeated the top poker player. Another example was Deep Blue, the chess program developed by IBM. It defeated Garry Kasparov, one of the greatest chess players.
11. Improving content distribution in the gaming industry with the help of AI
Creating high-quality Esports and gaming content requires a great content strategy. Gaming and Esports companies need to employ an effective team to create content. They also need to distribute this content to all the relevant channels including social media.
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Strategizing and creative tasks require expert human minds. However, Esports and gaming content creation and distribution have many low-end tasks too. A few examples are editing images and videos, and uploading them to social media platforms. Gaming and Esports companies can indeed automate these.
Blizzard Entertainment is automating these tasks. The company is using AI to revamp its content strategy. Blizzard Entertainment also plans to use AI to automate many of the content creation and distribution tasks.
12. Preventing cheating in Esports
The problem of cheating is common in many sports. It affects Esports too. Cheating creates several problems for Esports. Firstly, it adversely impacts the reputation of the game where cheating occurred. Secondly, cheating has a negative impact on the overall Esports environment.
Game developers have responded to this problem by creating anti-cheat software within their games. The effectiveness of these anti-cheat modules varies though. Players and fans noticed that some games lack effective anti-cheat modules. Furthermore, malicious players can find tools on the Internet to outsmart these anti-cheat modules.
AI can help to prevent cheating in Esports. AI-powered tools can monitor player behavior and identify suspicious patterns. ML can improve the process to detect suspicious behavior.
“2eggs”, a player of the well-known game CS:GO (Counter-Strike: Global Offensive) has developed an AI-powered tool called HestiaNet. It has already identified thousands of cheaters in CS:GO.
13. Improving ranking and matchmaking mechanisms with AI
Keeping records of Esports tournaments and leagues requires manual intervention, and it’s not fully automated. The ranking of players and teams depends on these results.
There can be manual errors in ranking, furthermore, there can be frauds. Matchmaking depends on this. Naturally, there can be errors and fraud in matchmaking.
AI can solve these problems. An AI-powered system can automate the record-keeping function in Esports. AI capabilities like ML and natural language processing (NLP) can eliminate manual intervention in the ranking of players and teams.
Furthermore, such an AI solution can match opponents of similar strengths. That will make tournaments and leagues more enjoyable.
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The best video and computer games that use AI are Middle Earth: Shadow of Mordor, Halo: Combat Evolved, S.T.A.L.K.E.R.: Shadow of Chernobyl, Gothic, F.E.A.R., Alien: Isolation, Grand Theft Auto 5, Bioshock Infinite, Half-Life, and Red Dead Redemption 2.
Game designers and game developers can use several game engines to incorporate AI in games. A few examples are Amazon Lumberyard, CryEngine 3, Panda 3D, Unity 3D, and Unreal Engine.
The best companies that use AI technology in games are APEX Game Tools, Blizzard Entertainment, DeepMind, Electronic Arts, Opsive, Spirit AI, and TruSoft.