All NPCs’ behaviors are pre-programmed, so after playing an FSM-based game a few times, a player may lose interest.Ī more advanced method used to enhance the personalized gaming experience is the Monte Carlo Search Tree (MCST) algorithm. If a player is attacking back, NPCs can ‘evade.’ If NPCs’ ‘healthpoints are low,’ they can go ‘find aid’ and then ‘wander’ again.Īn obvious drawback of FSM design is its predictability. If the player is out of sight, the NPC goes back to ‘wander.’ In other words, NPCs are always ‘wandering’ when you cannot see them. In this game, an NPC would begin with ‘wander’ status, and then engage in ‘attack’ if a human player is near (orange arrow). Figure 1: A simplified flow chart of how the Finite State Machine algorithm works in a shooting game. Many famous games, such as Battle Field, Call of Duty, and Tomb Raider, incorporate successful examples of FSM AI design. Even the turtles in Super Mario have a rudimentary FSM design. In this FSM-oriented game, a given character can perform four basic actions in response to possible situations: aid, evade, wander and attack. A simplified flow chart of an FSM is shown in the following image (Figure 1). For example, in a shooting game, AI would attack when human player shows up and then retreat when its own health level is too low. Basically, a FSM AI would promptly react to the human player’s action with its pre-programmed behavior. In a FSM, a designer generalizes all possible situations that an AI could encounter, and then programs a specific reaction for each situation. One of the most widely used tricks, called the Finite State Machine (FSM) algorithm, was introduced to video game design in the 1990s. Designers often use tricks to make these NPCs look intelligent. The most common role for AI in video games is controlling non-player characters (NPCs). Rather than learn how best to beat human players, AI in video games is designed to enhance human players’ gaming experience. However, the term “AI” in video game context is not limited to this self-teaching AI. AlphaGo was trained by observing millions of historical Go matches and is still learning from playing with human players online. This is true to some extent for AI like AlphaGo, which is famous for beating the best human Go players. The flashy vision AI described by these tech giants seems to be a program that can teach itself and get stronger and stronger upon being fed more data. Such argument has drawn a lot of public attention to the topic of AI. Recently Elon Musk has warned the world that the fast development of AI with learning capability by Google and Facebook would put humanity in danger. But how does AI found in gaming relate to the AI that tech giants talk about every day? Playing against an AI
AIs are often behind the characters you typically don’t pay much attention to, such as enemy creeps, neutral merchants, or even animals.
Regardless of whether you prefer race-car games like Need for Speed, strategy games like Civilization, or shooting games like Counter Strike, you will always find elements controlled by AI. If you have ever played a video game, you have interacted with artificial intelligence (AI). Figures by Shannon McArdel AI, the foundation of all video games
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