Generative agents for video games
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Smallville provides a framework for creating dynamic, memory-enabled non-player characters (NPCs) in video games, powered by Large Language Models (LLMs). It aims to reduce manual programming of NPC interactions by enabling agents to observe their environment, store memories, and react to state changes, leading to more realistic and engaging virtual characters. The project is suitable for game developers and researchers interested in AI-driven character behavior.
How It Works
Smallville leverages LLMs to simulate agent behavior, allowing them to perceive their surroundings, recall past experiences, and make decisions. The core approach involves an event-driven simulation loop where agents' states and memories are updated based on environmental changes. This contrasts with traditional scripted NPC behaviors by offering emergent, dynamic interactions driven by the LLM's understanding of context and memory.
Quick Start & Requirements
java -jar smallville-server.jar --api-key <OPEN_AI_KEY> --port 8080
.http://localhost:8080/dashboard
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Maintenance & Community
Licensing & Compatibility
Limitations & Caveats
The project is described as having an "example project" that is "not finished yet." The specific LLM models supported beyond OpenAI are not detailed, and configuration options for local LLM providers like LocalAI are mentioned but not fully elaborated.
1 year ago
Inactive