Artificial Intelligence In Gaming
The technology is boosting rapidly and has involved almost all the sectors of business and development. One of the major parts of the Industry – The Gaming Hub, is continuously modified and improvised by Machine Learning and Artificial Intelligence. This has brought a dynamic and powered upliftment in this sector.
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The world of Video Games is the most fascinating, enriched, and popular domain that every youngster wants. The passion for games has always seen an upward trend and is growing exponentially. There is a rising demand for realistic environments, sophisticated set-up, power play, and much more. From the beginning, this source of entertainment has revolutionized the industry and has brought loads of opportunities.
With such tremendous growth in the industry of games, it has been in the eye of developers. The industry of games started as a basic source of entertainment, with its main aim of involving people in a new virtual world of – Games! This was the start but now it has emerged as a different and modified sector. There are millions of developers, who are continuously trying to improve the games, introduce the latest technology, and make gaming awesome! There are thousands of games now.
It started with the introduction of Machine Learning when the machines were taught to learn on their own! At that time, the concept of involving this technology in gaming was also introduced. Machine Learning is a broad domain, so it was very difficult to train the bots in the games or make such a game for PlayStation. You all might remember, the “Pickachu Game” or “Shoot The Duck Game”, these were the starting steps in bringing machine learning into play.
With these games, the gaming industry started to revolutionize. This took an exponential curve and progress took place. After this there were so many games that involved trained bots, changing environments, increasing difficulty levels, new dynamic challenges, dynamic allocation of players, and much more. This all was very fascinating for the players. It required machine learning, neural networks, and the dominating part that played the most significant role is Artificial Intelligence.
Introduction of AI in Gaming
Artificial Intelligence made the games more interactive. The players began to increase. The new strategies in gaming brought by the introduction of artificial intelligence play a significant role in the establishment of a new level mark. The increase in technology advancement comes with the demand for its implementation in various sectors. This makes further development and progress possible.
There is a certain limitation in embedding games with artificial intelligence also. Most of the developers are concerned about using artificial intelligence in games. One of the main reasons for this is that they might lose their control over the enemy bots. They train the bots first but after that, they can learn, think, and react on their own.
This is what makes the games interesting. But many times it might also happen that the bots become uncontrollable and it ruins the game. So these things need to be considered while designing a game.
One of the oldest games that were designed using artificial intelligence is “Wolfenstein 3D”. In these games, the soldiers were designed using AI. The designer took care of what specific responses the bots can give, what different situations or environments can be introduced in the game. This was built with the help of – Finite-State-Machine (FSM) algorithm.
The Finite state machine algorithm might look simple to use but it is not possible to use this algorithm in every game. It comes with specific limitations. This is because the bots may follow the same pattern each time. This could generate a pattern that can be decoded by the player.
Then came another algorithm – “Monte Carlo Search Tree” (MCST). This algorithm solved the problem of generating a pattern. It analyzed all the possible states in which the bot can go, i.e., all the possible moves of the bots. Then it generated all the possible outcomes of the specific input state of the bot. With each turn, the computer initiates the process of creating a new set of input states and the relevant output state. This was the most popular algorithm at that time.
You can visualize it by imagining that the computer is given a specific situation and depending upon that situation it can generate a set of choices that would be taken as input. And then, depending on each input, the computer can generate a set of specific outputs. There would be a specific set of outputs for each input. In this way, with the changing environment, the computer has to do all this calculation again.
This all involves lots of calculations that the computer needs to do with each changing state. But for each environment, the bot will choose any random case.
Behavioral Decision Trees
One of the most important things the developer requires while designing a game is a proper and efficient format of decision making. This can be made effective, efficient, and easier by the use of the Behavioral Decision Tree. The structure is like a tree with various selector nodes which help in taking proper decisions.
The tracing of the behavioral decision tree follows a specific pattern. Its traversal is from the left to right. The decision sequence follows from the steps taken in the sequential order from left to right. The steps are followed in serial order. If any steps are wrong or can’t be taken then the step is reverted to the initial state. By this, the sequence will come to an end, and then it would require to start the processing again.
The result is given back to the parent node. With the introduction of each layer, in multi-layered decision making, the complexity of decision making increases. In between the sequence nodes, there might come a selector node followed by another sequence node. This gives an option to the bots to select other pathways. In this way, there are multiple choices for the bots.
One of the games that make decisions based on the Behavioral Decision Tree algorithm is the Alien A.I. In this game, the bots start from a particular selector node and follow a sequence. In this sequence, there are various selectors so that the path taken by the bot would be a dynamic one. In this game, the actions of the alien were controlled.
This is the most essential technology when it comes to gaming. The world of games is incomplete without the introduction of neural networks. There are two widely used categories of neural networks – genetic neural networks and generational neural networks. These help in training the bots or the players that how to perform a specific task. You can think of a situation where a player has to find a certain destination or follow a map. In that instance, neural networks help to design the player in such a way that he can take maximum decisions himself.
This also helps in making various decisions like what action should the player perform like aiming for a target when the player has to shoot. The generational neural networks provide much better visualization. These are similar to standard neural networks but way too better than them.
These networks consist of a set of input nodes that are linked to other nodes via a hidden layer. Each input node is connected to another node and that is connected to some other node. In this way, they form a channel of nodes that propagate through the hidden layer.
The generational network works by calculating the size that each set of cases would have. Suppose in a particular game we can have as many players as we want in the first stage. So it would evaluate the possibilities of players remaining as the output of different circumstances like shooting, surrendering, etc.
Various games use the – Reinforcement Learning technique. The most popular game series that uses this technique is: “Grand Theft Auto” or widely known as GTA. This game includes various environments, players, cars, houses, etc. It includes the view of a whole city and it has more than one city. The city is generated automatically as the player moves forward. This is one of the major specialties of this game.
The player can move, run, shoot, eat, and do lots of other activities. The bots are generated automatically, the police arrive whenever any rule is broken, there are various other stations like an ordinary city has. All these things require reinforcement learning and artificial intelligence.
There are many other games like Call of Duty, Clash of Clans, PUBG, etc. that use various technologies like machine learning, neural networks, reinforcement learning, and artificial intelligence. With the use of these technologies, the games become interactive and have the scenario and conditions relevant to the real world. This makes the players more enthusiastic about the game.
One can never forget the game – Super Mario. All the game enthusiasts have played this game at least once in their life. This game was originated due to the curiosity of developers who tried to put artificial intelligence in gaming through an algorithm. This is one of the most popular games and is one of the best examples of artificial intelligence at the initial level, i.e., when the introduction of artificial intelligence in gaming had just started.
One of the biggest examples of artificial intelligence in gaming is the game – Pokemon GO. It includes our real-time environment and according to that, it places a pokemon in the pathway which we need to find. This makes the full of fun. The player has to search for the pokemon in his surroundings and catch it. There is a deep learning technique associated with the implementation of this game. It helps the players to connect the game with their surroundings.
The developers are continuously thinking of innovative ideas that could merge the software and hardware, and with the use of artificial intelligence, design an amazing game. The main efforts are on the demands of the players to make a real-world based game, i.e., the game should relate to the real world. This shows that the introduction of artificial intelligence has increased and broadened the sector of gaming.
Video Games are the major source of attraction. Mostly the players want to play on a PlayStation. This has increased the demand for innovative video games. This is the current situation of the market, with loads of games available, the increasing demand is for more interactive, innovative, and real-world like games.
This pacing demand indeed has set a challenge for all the game developers. They need to work hard to implement a game using artificial intelligence that would satisfy maximum players. The developers can use the combination of various technologies available. This might give rise to any new technique that would revolutionize the sector of gaming once again.
The future scope of Artificial Intelligence in gaming is wide. There are many fields in gaming that need attention and proper implementation. Right now, developers want that after using artificial intelligence, the control over the bots should not get lost properly as it will cause various loopholes in the game.
So one challenge is to overcome this thing. The other thing is to upgrade gaming based on the latest technology available. This will cause a tremendous rise in the gaming sector and would emerge as a boon for technological development and digitalization.
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