A Survey on Large Language Model-Based Game Agents
📰 ArXiv cs.AI
Learn how Large Language Models (LLMs) are used to create game agents with generalizable reasoning and adaptability
Action Steps
- Read the survey to understand the current state of LLM-based game agents
- Apply LLMs to game environments to test their generalizability and adaptability
- Configure game agents using LLMs to improve their reasoning and memory capabilities
- Test LLM-based game agents in various game environments to evaluate their performance
- Compare the results of LLM-based game agents with traditional game agents to identify areas of improvement
Who Needs to Know This
AI researchers and game developers can benefit from this survey to understand the capabilities and limitations of LLM-based game agents
Key Insight
💡 LLMs can be used to create game agents with improved reasoning, memory, and adaptability in complex game environments
Share This
🤖️ LLMs are being used to create game agents with generalizable reasoning and adaptability! 🎮️
Key Takeaways
Learn how Large Language Models (LLMs) are used to create game agents with generalizable reasoning and adaptability
Full Article
Title: A Survey on Large Language Model-Based Game Agents
Abstract:
arXiv:2404.02039v5 Announce Type: replace Abstract: Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable testbed for exploring capabilities relevant to Artificial General Intelligence. Recently, the emergence of Large Language Models (LLMs) provides new opportunities to endow these agents with generalizable reasoning, memory, and adaptability in complex game environments. This survey offers an up-to-date
Abstract:
arXiv:2404.02039v5 Announce Type: replace Abstract: Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable testbed for exploring capabilities relevant to Artificial General Intelligence. Recently, the emergence of Large Language Models (LLMs) provides new opportunities to endow these agents with generalizable reasoning, memory, and adaptability in complex game environments. This survey offers an up-to-date
DeepCamp AI