Artificial intelligence (AI) is used often in video game development to create characters that mimic intelligent behavior using machine learning. These AI systems are designed to understand the strategy and complexity of a game and its rules to engage players with dynamic challenges and immersive experiences. 

However, AI can be used to create more than just complex challenges for players. It can also improve non-player characters (NPCs) and create more intricate environments for players to explore, delivering greater depth to video games. So, how is AI being used for character and behavior designs in video games?

The Impact of AI on Character Design

Traditionally, character design in video games is a static process. Designers first conceive of a character, their role and purpose, and how they will interact within the game’s environment. Normally, however, these characters are designed in a fixed state, following a certain set of rules with a list of responses that they can deliver to the player, unlike tabletop games where NPCs can have variable interactions with characters through DM systems. 

AI introduces a layer of complexity to character design, allowing for greater realism and human-like movements. Deep learning can be applied to visual development using convolution that analyzes grid data to make more realistic facial expressions and visual appeal. 

However, emotional intelligence and improved language abilities are really what makes AI exciting for video game development. Natural language processing (NLP) and affective computing can be combined to create NPCs that are able to hold high-end conversations with players during quests that reach beyond traditional branching dialogue trees. 

Adaptive behaviors and other intelligent designs can also be implemented to create NPCs that are able to learn from a player’s actions, helping them learn how to create better challenges. This level of personalization can be applied to nearly all genres of video games from RPGs and FPS games to sports and more. 

AI in Behavior Design and Game Play Experience

AI can enhance the overall gameplay experience by adding strategic depth to a game. Machine learning algorithms inside a game can identify strategic patterns used by players that can then be exploited by the AI. This cause and effect forces players to adapt to the game’s increasing difficulty, leading to more immersive gameplay. 

Dynamic game environments controlled by AI can also establish more engaging content for players, especially in games where weather plays a significant role in decision making such as racing simulators and survival games. AI also makes destructible environments more realistic too, creating areas in a game that can respond to players’ actions like explosions or resource gatherings. 

Benefits of Utilizing AI in Gaming

AI is becoming a major resource for game developers, using it to create more enjoyable games for players. As AI technology advances, more improvements are becoming apparent. They include:

• Adaptive gameplay: Machine learning algorithms can analyze a player’s play style and use it to modify NPCs strategies for dynamic challenges. This can cause players to form new strategies using other components of gameplay that they may have been ignoring. 

• Intuitive interactions: NLP can be used to create highly conversational NPCs, providing players with unique dialogue options that are not present in pre-designed dialogue trees. 

• Personalized content: Games that are rich in lore and roleplaying can use pattern recognition and radiant quests to lead characters toward dungeons that are more suited to their class and abilities. 

• Enhanced storytelling: AI can help players experience less linear gameplay, adjusting the world around their characters’ interactions with the game’s plot and characters for greater replayability. 

• Dynamic environments: Generative adversarial networks are commonly used to create procedurally generated content that leads characters to new dungeons and side quests that are not part of the primary plot or map. 

AI and Monetization

Ethical concerns begin to appear when AI and dynamic difficulty are combined with monetization strategies that have become commonplace, especially in sports games and mobile apps. By using AI to raise the difficulty, players are forced to try new strategies and ideas to succeed. However, modern gaming has implemented new features that require players to purchase in-game items and bonuses using real money which has been angering gamers for the past decade. 

Without having an appropriate alternative to monetization and microtransactions, dynamic difficulties cause players to hand over more cash to enjoy a game they’ve already purchased. While games still try to offer options that don’t involve microtransactions, they tend to be extremely timeintensive and force players to “grind” the game. Some examples of this can be seen in the FIFA series and their Ultimate Team modes and Diablo Immortal which have both received massive criticisms for their use of microtransactions. 

Future Trends

AI poses a lot of exciting opportunities for experimentation. Game developers are always looking for new ways to design games and offer unique experiences to players and, with a growing number of gaming applications like AR/VR and streaming, there are some unique ways for AI to be used in the future. 

Generative AI is an exciting new technology and has the potential to recreate tabletop RPGs like Dungeons and Dragons by automating the Dungeon Master and providing players with a real chance at a single-player version of the popular game. Couple that with the ability to walk through our favorite virtual worlds with VR and the future of gaming looks brighter than ever.