ReAct (Reasoning and Acting) agent built from scratch in Python, adapted to interact with Microsoft’s TextWorld environments.

This dataset contains sequences of states generated by playing Microsoft TextWorld. Each state contains graphs, descriptions, previous action and valid actions.

A repo for my MSc project

twagents is a framework for building and comparing language model agents with different memory architectures in interactive, text-based environments. It is designed to work with TextWorld and focuses on exploring how working, episodic, and semantic memory influence agent behavior, recall, and decision-making.