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For many applications of LLM agents, the environment is real (internet, database, REPL, etc). However, we can also define agents to interact in simulated environments like text-based games. This is an example of how to create a simple agent-environment interaction loop with [Gymnasium](https://github.com/Farama-Foundation/Gymnasium) (formerly [OpenAI Gym](https://github.com/openai/gym)). |
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| .. | ||
| agent_simulations | ||
| agents | ||
| autonomous_agents | ||
| chatbots | ||
| code | ||
| evaluation | ||
| question_answering | ||
| agent_simulations.md | ||
| apis.md | ||
| autonomous_agents.md | ||
| chatbots.md | ||
| code.md | ||
| evaluation.rst | ||
| extraction.md | ||
| personal_assistants.md | ||
| question_answering.md | ||
| summarization.md | ||
| tabular.md | ||