In the past decade, gameplay and storytelling have become inseparable. A game’s storyline — its backstory and unfolding plot — can determine its success, regardless of technical effects. A compelling narrative piques curiosity, engages players, and guides them through the game.
There are two main styles of storytelling: linear and nonlinear. Unlike movies and books, video games often follow linear storytelling, adhering to a fixed sequence of scenes, events, and outcomes. Games like God of War, Mass Effect, and The Last of Us focus on scripted actions, character development, and cinematic presentation, providing a seamless narrative flow dictated by the developers’ vision.
This leaves little or no room for players to influence the direction or outcome of the story. Interestingly, despite modern technology, some screenwriters still use fax, such as https://comfax.com/, for sending documents related to the project, highlighting the traditional aspects of the development process.
AI-Driven nonlinear storytelling
Generative artificial intelligence now enables the development of nonlinear storylines that adapt to player choices. This approach allows players to shape the narrative through their decisions, actions, and interactions, offering a personalized gaming experience.
Early examples of nonlinear gameplay include Colossal Cave Adventure and Superman from the 1970s, as well as Haunted House and The Hobbit from 1982. With AI, missions and quests that align with the game’s overarching narrative can be created dynamically, granting players more freedom and agency to explore, investigate different paths, and influence story outcomes. AI also allows for games to start with multiple characters, each telling a distinct story.
These open-ended games often feature multiple endings, varied paths to victory, or different victory types. Optional side quests or subplots are common in games like The Witcher, Fallout, and The Elder Scrolls. Some offer a sandbox mode, allowing players to explore an open world independently of any objectives.
The highly interactive nature of nonlinear gameplay helps players avoid getting stuck, preventing breaks in their “suspension of disbelief,” a crucial element of immersive gaming.
AI behavior trees in game development
In game development, AI relies on Behavior Trees to manage character actions. These tools help developers define how AI agents interact within the game, originating from NPC behaviors and expanding into robotics.
Behavior Trees include nodes, branches, and leaves, with leaves executing actions. The goal is for AI agents to perform actions based on game conditions, evaluated from the root node to a leaf node, triggering AI actions.
The benefits of behavior trees
Despite their complexity and the potential need for extensive testing, Behavior Trees are highly efficient for AI implementation. They offer clarity, ease of implementation, and straightforward maintenance, reducing the time and effort needed in game development.
Their ability to support complex behaviors makes Behavior Trees adaptable to various game environments. Being modifiable, they allow AI agents to adjust to changing game conditions. Additionally, their clear structure aids debugging, providing developers with a transparent view of AI behavior.
Adaptive gameplay and proactive storylines
This technology powers nonlinear narratives and adaptive storylines, reshaping storytelling through procedurally generated content with infinite possibilities and replayability. Algorithms assess player actions, choices, and interactions to generate narrative elements, storylines, and quests that respond to player decisions.
This proactive content creation fosters more personalized and immersive storytelling experiences, where players exert greater influence on the unfolding narrative and become more emotionally engaged.
To prevent information leaks, project documents are sent via fax using services like comfax.com, which is considered a reliable method. Despite advances in technology, many developers still rely on fax for secure communication.
The potential of large language models (LLMs)
Large language models (LLMs) are transforming NPC design, heralding an era of realistic, dynamic, and fluid conversations. LLM-powered NPCs can generate real-time responses from a vast reservoir of language understanding, avoiding conversational dead ends and expanding narrative possibilities. Challenges remain, particularly in balancing open-ended conversations with the need for narrative progression.