gaming
Five AI tools every game developer should have in their toolbelt
The games industry is no stranger to Artificial Intelligence (AI) in video games. Anyone that’s played a game populated by NPCs or multiplayer games with bots will know that the quality of the AI that defines how they interact with players can be hugely variable. Done well, AI-controlled characters help a game to be more cohesive and engaging.
That’s why research into game AI is an ongoing focus for so many studios, with bigger companies such as Sony exploring advanced AI techniques like reinforcement learning, which has the potential to create the most advanced form of NPCs to be a player’s friend or foe, depending on how they play.
But AI’s capabilities don’t stop there. AI is also changing the way games are developed, adding much greater realism to in-game characters, gaming experience and creating autonomous online bots that are near-indistinguishable from human players.
Electronic Arts is currently developing systems that use machine learning to replicate facial expressions, skin types and body movements from video and photos. In theory, this means that actors would no longer have to come into a mo-cap studio and there would be a greater range of genders and ethnicities produced in games.
With so much happening in this space, we’ve compiled a list of five AI tools every game developer should have at hand to make their lives easier.
Content Generation
One of the most time-consuming processes a developer will have to deal with is content generation, especially in puzzle games where there is a high demand for new levels. But AI technology can help here, using a method known as Procedural Content Generation (PCG), which creates content algorithmically. AI can be used to generate tens or hundreds of variations ready to be reviewed and selected. If the AI is being used for level generation, it’s even possible to use AI bots to play the levels and score them for difficulty or the time it takes to complete them.
PCG allows for quicker content creation and provides developers with more time for creative experimentation. The AI can easily do the heavy lifting, but human input is still crucial to launching a polished product, which is where the developer’s skill comes in.
Testing
Unlike mobile apps or web pages, games are one of the hardest forms of software to test due to their sheer variation, the near-infinite number of states a game can have, its custom interaction models, and constant updates.
Games are still mainly tested by humans, which means it can be a lengthy and expensive process. While big studios have the budget to create dedicated teams that focus solely on game testing, smaller developers mostly rely on their network of friends, coworkers and fans. But what happens when they are unable to test every aspect of the game? That is where AI and machine learning steps in.
Testing in video games is complex due to the number of split-second choices a player can make and the outcomes those choices have. In addition, there are interactions with other human and non-human players that are also non-deterministically playing the game, which further complicates things.
The advantage of using AI bots for your playtesting is that they can test quickly, constantly and methodically. For example, bots can be used to test for things like object clipping by running all the possible moves and interactions on a level far faster than a human player..
Cheat Detection
Cheating turns players off multiplayer gaming, even if they are not directly affected. For players striving to be the best, it’s all too easy to turn to cheat tools that bestow superhero-like powers in the game. Cheating tools range from simple aimbots that assist with aiming and shooting in FPS games like CounterStrike to mining bots in MMOs that control a player’s character and essentially play for them.
Developers can combat the use of cheats with machine learning and behaviour-based detection AI. By collecting data on a player’s behavioural patterns, such as how a player moves the controller or how fast a player reacts, AI can recognise when an action goes beyond normal human behaviour.
While there are plenty of other products that are able to detect cheaters, the advantage of a machine learning system is that it’s continuously learning and adapting itself to fit the game – making it harder for players to fool. This means that developers can employ updates and patches to the game without having to reprogram the AI.
Content Moderation
Online toxicity has become a growing problem as more and more games are built around persistent online worlds with thousands of concurrent players. There are times that a small number of players spoil the experience for the majority. However, AI is a great ally for developers looking to curb such behaviours and safeguard their players.
There are different approaches to moderating game chat. The most common is to use lists of banned words and phrases, which can be used to block posts that use them. The problem here is that gamers can get around moderation by changing letters to numbers or using slang phrases.
A better approach is to use an AI model that can consider the context of the text so that even if a player is being clever with the spelling of a word, it will still be flagged due to its context and intent. This kind of AI is relatively recent, with only a handful of experts working in this field. But, with no signs that toxic behaviours are declining and the number of people playing games increasing, this is a field that will continue to need expert solutions.
Whilst, AI can capture the bulk of comments before they are posted, human moderators are still required as the ultimate arbiters of what content is permissible. But working as a team, human moderators and AI moderation can together ensure that games are a safe space for all players.
AI Player Stand-Ins
The big attraction of online games is the ability to interact and team up with other players. However, there are not always enough human players to fill in the empty seats; that’s where bots come in.
Bots can act as a reasonable stand-in for human players, with a sophisticated range of behaviours. But it’s still pretty obvious to most when you are playing alongside a bot rather than a real person
One way to address this is to use AI to introduce more variables into the behaviour of the bots. This can give a much more realistic impression of unpredictability, and reproduce things like the risk-taking that you often encounter with human players.
While the combination of techniques used to create effective AI-based bots is fairly new, when done correctly it can create dynamic, adaptive and very human-like bots that add an extra dimension to online play.
AI tools are there to help developers
Developers are faced with an immense amount of challenges to develop great games very quickly, but thanks to the latest AI-based tools, there are powerful solutions to some of the most resource-hungry aspects of the development process.
That is why AI is increasingly becoming an essential addition to the game development process, providing developers with the tools, and the insight, to address any issue that arises. Which, in turn, allows them to unload tedious tasks and concentrate on creative output.
About modl.ai
Headquartered in Denmark, modl.ai is a team of game developers, engineers and AI experts working together to create AI-driven tools for building better games. Its AI-based tools allow developers to rapidly create and test games and understand their players. modl.ai’s unique technology is designed to accelerate the game development process, automating repetitive and time-intensive tasks and helping developers to enhance and increase player engagement.
modl.ai was founded in 2018 by Christoffer Holmgård, Benedikte Mikkelsen, Lars Henriksen, Sebastian Risi, Georgios N. Yannakakis, and Julian Togelius, who between them have been involved in the launch of more than 30 games and have more than 28,000 citations in technical literature covering AI and game design. In 2019 the company successfully secured seed funding from a number of investors led by PreSeed Ventures, Denmark’s largest and most successful early-stage investor, joined by Saltagen Ventures and Propagator Ventures.
gaming
Getting ready for Xmas: SplitMetrics partnership with Wargaming helps World of Warships app sail to new heights with 15% uplift in organic conversions
The post Getting ready for Xmas: SplitMetrics partnership with Wargaming helps World of Warships app sail to new heights with 15% uplift in organic conversions appeared first on European Gaming Industry News.
gaming
Nolimit City revisits the brutal factory life in Outsourced: Slash Game
Nolimit City takes you back to the grind with its latest release, Outsourced: Slash Game. For those who thought their consumerist cravings were a safe indulgence, think again. Following in the footsteps of Outsourced, this new addition pulls back the curtain on the sweat and sacrifice lurking behind those everyday luxuries—this time with a dash of danger. Outsourced: Slash Game is the studio’s second venture into crash-style gameplay, the first being xCrash™ in Skate or Die – but this time it’s a standalone crash game!
In Slash Game, players have to make some cutthroat decisions as a laser traces the outline of their hand, increasing the multiplier with every pass. Players hit “stop” to cash out, locking in the multiplier when they feel the timing is right. After which, they will be shown the potential winnings if they wouldn’t have stopped. But here’s the catch: if players hesitate a second too long and the laser slips, all the winnings are lost. A live scoreboard displays the Top Win, Top Miss and Last Round, so that players can keep track of their previous rounds.
Outsourced: Slash Game is not a familiar Nolimit City slot to some players but could cause some excitement with an increasing multiplier and a maximum payout of 1,500x the base bet. Outsourced: Slash Game, unlike Nolimit City’s high-volatility slots, is rated as ‘Medium Volatility’ but don’t let that fool you as it still includes the risk of losing your hand.
Per Lindheimer, Head of Product at Nolimit City, said: “Get back to work, will you? We’re bringing players back to the unrelenting factory floor of Outsourced with an all-new twist. Slash Game is a standalone take on our crash-style games, and it’s packed with plenty of heart-stopping moments (and maybe a few hand-stopping ones, too). We’re thrilled with how it turned out and we hope that our fans will be too!“
‘Outsourced: Slash Game’ will be available to all Nolimit City partners on November 5th, 2024.
The post Nolimit City revisits the brutal factory life in Outsourced: Slash Game appeared first on European Gaming Industry News.
CS2 Intel Extreme
CS2 Intel Extreme Masters Rio 2024 SuperComputer: NaVi to bounce back after Blast Fall Final loss
Final: Natus Vincere (36.5%) to beat Team Vitality (28.1%)
Semifinal 1: Natus Vincere (52.6%) to beat MOUZ (16.3%)
Semifinal 2: Team Vitality (47.7%) to beat G2 Esports (18.7%)
Quarterfinal 1: G2 Esports (39.8%) to beat FaZe Clan (32.8%)
Quarterfinal 2: MOUZ (35.9%) to beat Eternal Fire (24.7%)
Group stage:
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Natus Vincere – 48.7% to finish 1st; 17.0% to finish 2nd; 84.1% to make playoffs
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Team Vitality – 40.8% to finish 1st; 17.4% to finish 2nd; 77.7% to make playoffs
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G2 Esports – 19.3% to finish 1st; 20.4% to finish 2nd; 56.7% to make playoffs
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MOUZ – 14.5% to finish 1st; 21.8% to finish 2nd; 53.0% to make playoffs
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FaZe Clan – 13.9% to finish 1st; 21.0% to finish 2nd; 50.2% to make playoffs
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Eternal Flame – 40.7% to finish 1st; 16.2% to finish 2nd; 40.7% to make playoffs
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Liquid – 16.3% to finish 7-8th; 35.7% to make playoffs
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Virtus.pro – 15.4% to finish 7-8th; 29.9% to make playoffs
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Astralis – 28.9% to finish 9-12th; 31.5% to make playoffs
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The MongolZ – 32.7% to finish 9-12th; 25.4% to make playoffs
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Complexity – 34.3% to finish 9-12th; 21.2% to make playoffs
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Heroic – 26.8% to finish 9-12th; 23.5% to make playoffs
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paiN – 36.5% to finish 13-16th; 21.0% to make playoffs
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FURIA – 36.4% to finish 13-16th; 20.9% to make playoffs
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9z – 44.7% to finish 13-16th; 14.6% to make playoffs
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Imperial – 49.1% to finish 13-16th; 13.9% to make playoffs
It has been quite the run for NaVi despite their loss with back to back grand finals in recent weeks but CSDB.gg’s predictive model suggests there will be no let up for the Ukrainian esports organisation.
G2 will also be looking to build more momentum in preparation for Majors season with NiKo on a quest to finally get over the line this year to win his first major title. Hopefully Rio won’t have to see a repeat of his reaction in the semifinals at BLAST Premier Fall Final 2024 where he punched a hole in a table after losing out to Team Vitality in a key moment.
However, the hosts of Intel Extreme Masters Rio 2024 may want to lockdown any nearby furniture and reinforce their desks if G2 are set for disappointment at the semifinals stage as predicted by the CSDB.gg SuperComputer.
A victory in Rio could be even more consequential for how the end of the year shapes up for the leading teams on the circuit. The Valve Global rankings have both teams close at the very top (NaVi at 1988 and G2 at 1953) meaning a win for either team could hand them a key advantage when it comes to who enters the Majors as top seed.
Back-to-back wins in T1 events for G2, should they prosper in Rio, would set the Berlin-based team on an incredible trajectory going into the winter months.
Meanwhile, Brazilian hopes for glory look slight according to the CSDB.gg SuperComputer with FURIA, the team co-owned by Neymar, having only been given a 20.9% chance of even making the playoffs.
They are the leading contenders to make an impact for the home crowd but there are other teams flying the flag for Brazil with paiN and Imperial also set to give it their best to give local fans something to cheer on.
In terms of forecasted matchups of note, G2 and FaZe Clan could offer up a fascinating encounter in the quarterfinals should both teams qualify, with each organisation rated as having a strong chance of making the semis with little to separate them should they meet.
How was the CSDB.gg CS2 Tournament SuperComputer created?
The CSDB.gg CS2 Tournament SuperComputer is a predictive model created using world ranking points, team quality ratings and performance trends. An element of randomness is also included in the model to avoid the best teams and players always winning, to reflect the fact that upsets can happen.
Every tournament is simulated 1,000 times with the results aggregated into a percentage rating of the chances teams or players have to achieve the predicted result.
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