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Ways through which ML will be leveraged in video games

Machine learning is spearheading revolutionary breakthroughs in nearly every industry and business vertical, serving as somewhat of a revelation which is a part and parcel of Industry 4.0 Ranging from agricultural planning to cancer diagnosis in medicine, machine learning, or ML has a wide range of applications. These subjects are typically more broadly talked about as they are already having an influence that is discernible and good for human beings as a whole. However, with regards to the billion-dollar video gaming industry, machine learning being leveraged in the process of game development remains in a nascent stage and has not been making headlines in the same way as the other use-cases that we previously talked about. In this blog post by AICoreSpot, we will discuss how machine learning will incite a revolution with the domain of video game development. 

To get a perspective of the scale and scope of the video gaming field, according to Newzoo’s Global Games Market Report, the gaming industry has attained a global worth in excess of both the film and music industries clubbed together. This is monumental.  

In totality, across mobile, console, and PC gaming, video gaming has attained a user base of 2.3 billion gamers active, internationally. One quarters of our planet’s populace stated that they’d played a video game in 2018. What this means is that video gaming is one of the most widely-reaching variants of entertainment ever. 

AAA titles in games can pull in billions of dollars for game production enterprises. Take for instance, Grand Theft Auto V. It is the most profitable entertainment product of history, raking $6 billion in revenues, easily surpassing all films, television shows, and music with regards to total revenue. Grand Theft Auto’s remarkable success, and the success of other famous titles which includes smartphone games such as Angry Birds or Candy Crush, is mostly based on how comprehensively the game can develop a world, immerse the user, and provides, tens, hundreds, or even thousands of hours of unique gameplay content. 

ML in game development 

For our readers who currently don’t have a very precise understanding of what Machine Learning is, go back and read some of our blog posts on the topic. They provide you with well researched content on the ins and outs of machine learning as a technology, and what exactly you can accomplish with it. And its scope is tremendous, to say the least. For the others who want a brief summarization of the technology right now, here goes: “Machine learning, or ML is the capacity of a system to learn and evolve from experiences, without being overtly coded or programmed.” ML is also known as AI and falls under an umbrella of technologies that make up the broad terminology, artificial intelligence. 

Why has machine learning witnessed a meteoric ascension in the past half-a-decade? This is owing to major enhancements in graphical processing unit speeds and the humongous amount of data that is available for ML and deep learning algorithms to train themselves on. 

Machine learning, hence, could exert a major influence on the way video games are produced. In the mission to generate more authentic looking worlds that the player can explore, developing interesting challenges that the player has to overcome, and in providing sophisticated and unique content, video game development companies are looking at leveraging nascent technologies such as machine learning to enhance the developmental process. Machine learning algorithms can react to a user’s actions in a dynamic fashion. Whereas everything in modern video games must be scripted by hand, games encoded with a machine learning engine could react and alter how the world, non-player characters (NPCs) or items act in real-time, on the basis of the user’s actions and decisions. Facilitating games developed with machine learning to respond more dynamically and in more creative ways to the player. This undeniably plays a huge part in increasing player engagement and in increasing the game’s popularity. The more interactive, dynamic, user-friendly, and fun a game is, the more the number of people that are going to flock to it. It’s that simple. 

Artificial intelligence in gaming 

Why are game developers seeking to leverage artificial intelligence in game production? There are basically two issues in game development circles that ML can tackle in several ways. 

  • Playing the game vs., or in collaboration with other human players 
  • Assisting to develop the game in a dynamic fashion for players 

We’ll look at the possible solutions for these two categories below, but typically, machine learning algorithms can outsource a lot of the functions that a human game developer is presently required to execute. Control of NPCs and the development of unique settings could all undergo automation if we can produce reliable algorithms for them. 

There’s definitely potential for machine learning in gaming, but we’ve only just begun to scratch the surface of all of the potential applications where it could be relevant. CEO of Epic Games, Tim Sweeney has stated “Video game AI still remains in the dark ages.” 

Although, once ML attains a certain level of maturity that can be dependably leveraged in gaming, it could drastically alter the gaming experience in several ways: 

  • Algorithms playing the part of NPCs 

Non-player characters will react to your gameplay in novel, innovative ways, keeping players at the edge of their seats. 

  • Modelling of complicated systems 

The game could forecast and modify downstream effects. 

  • Increasing the beauty of games 

Textures and objects will have dynamic rendering as you get in closer proximity to them. 

  • More authentic interactions 

Natural language processing will facilitate more authentic conversations and responses. 

  • Universe creation on the fly 

Open-world games have the possibility to be limitless in size. 

  • Smartphone games with increased engagement 

Artificial intelligence chips in smartphones will provide the power of machine learning to smartphones. 

1.Algorithms playing the part of NPCs 

Currently, your rivals in a video game are pre-scripted non playable characters, however, an ML-driven NPC could enable you to play against less-predictable enemies. These enemies could also alter their difficulty level based on how well, or how badly, you are playing the game. As you get more adept at the gameplay, your foes could become more intelligent and react in innovative ways based on your behaviour and gameplay within the game world. 

Organizations are already working on preliminary applications of ML-based NPCs. SEED by EA undertakes training o NPCs by emulating top players. Its non-player characters go about learning dynamic ways to move within the game world, and actions, and leveraging human player’s actions as the training data means the algorithm undergoes training four-fold quicker in comparison to just leveraging reinforcement learning. 

Trainable non-player characters are a non-trivial enhancement with regards to game development. Presently, game development outfits spend thousands of man hours scripting these non-player characters. Not hard-coding these non-player characters could minimize the development cycle for a game considerably. From weeks to a matter of mere hours. 

2.Modelling of complicated systems 

A ML algorithm’s plus point is its capacity to model complicated systems. Video game developers are always attempting to get games to have increased levels of immersion and realism. These are the cornerstones of player engagement. Obviously, modelling the physical world is a humongous task, however, an ML learning algorithm could assist with forecasting the downstream impacts of player’s behaviour or even modelling stuff the player cannot alter, like the weather. 

One present instance of complicated modelling in production at the moment, is FIFA’s ultimate team mode. As you choose your team of all-star soccer players, FIFA quantifies a team chemistry rating on the basis of how much the personalities on your team might gel together, or not. In the course of games, team morale can tank if you’re not winning or are making small errors. It can also appreciate drastically when the audience cheers you and you’re performing well. The modifications in morale influences the player’s capabilities, in-game. More errors happen when morale is low, and skill shots and lucky breaks occur more often when your team is performing well together. 

3.Making games prettier 

Another aspect of providing more realism to games is making them look beautiful. Game developers are also leveraging machine learning in this aspect. In video games, typically things appear good from a distance, but when you get closer, objects have a tendency to pixelate, and are rendered poorly. There are exceptions, however. 

Microsoft is collaborating with Nvidia to rectify this issue. They’re leveraging machine learning to improve images and renderings in a dynamic fashion. In real life, when you’re distant from an object, the details aren’t obvious, but as you get closer in proximity, you can see the fine details. This dynamic rendering of the minute details is a hurdle that computer vision algorithms can overcome. 

4.More Authentic Interactions 

Another dominant hurdle in developing an authentic virtual world is how users interact with friendly NPCs. In several games, you are required to talk to scripted characters in order to finish your objectives. But these conversations are restricted in scope and typically adhere to on-screen prompts.  

Leveraging natural language processing could facilitate you to talk out loud to in-game personalities and get authentic reactions, just like conversing with Siri, Alexa, or Google Assistant. Additionally, games that integrate virtual reality haptics or imaging of the user could enable computer vision algorithms to identify body language patterns and intent, further improving the experiences of communicating with NPCs. 

5.Universe development on the fly 

One of the applications with the most potential with regards to the application of machine learning in video gaming is world development on the fly. Presently few of the most famous video games are expansive open-map games that enable you to explore a humongous landscape. Those games need thousands of hours of developer and artist input to render effectively. But ML algorithms could assist with pathfinding and world development. An instance is a video game like No Man’s Sky which contains a limitless number of new worlds to discover, all produced on the fly as you explore the vast universe. This strategy is referred to as procedural generation, and the contents of the universe, and the player experience will be unique each time you begin a new space-faring quest. 

6.More engaging smartphone games 

Smartphone gaming makes up half of the gaming industry revenues, internationally. Games on your smartphone or tablet device are simple to pick up and play, when you have free time, without the requirement of owning a dedicated console or gaming PC. Historically, smartphone games were restricted in scope as earlier iterations did not possess the computational capabilities and graphics of a console or PC. But these restrictions are beginning to fade, with AI chips in latest smartphones that add extra processing prowess. Several of the advantages of machine learning will become available to smartphone games, and in addition, the hardware continues to evolve on an ongoing basis, making smartphone gaming more authentic, interactive, engaging, and immersive – potentially rivalling desktop and console games in the process. 

The outlook for machine learning within video game production 

There are still dominant hurdles facing machine learning applications in video gaming. One primary obstacle is the lack of information to learn and evolve from. These algorithms will go about modelling complicated systems and actions, and we don’t really have adequate historical information on these complex interactions. Additionally, the machine learning algorithms produced for the video gaming industry are required to be foolproof. They cannot impact the game negatively or the user experience. This means that the algorithms are required to be precise, however, they must also be quick and seamless from the user’s viewpoint. Anything that slows down or impacts the game architecture negatively is immersion breaking and pulls the player out of the universe that game developers have lovingly crafted. 

Having said that, most leading game production companies have an extensive number of teams undertaking research, refining, and application of artificial intelligence into their products. This is a hurdle that several organizations are working on as it puts forth such a thrilling opportunity to get video games into newer horizons, providing players with even more authentic experiences and more comprehensive, playable content. 

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