Letting Claude Play Text Adventures (borretti.me)

At a recent AI hackathon, a developer explored the potential of cognitive architectures in enhancing the performance of large language models (LLMs) like Claude Code through text-based adventure games. By adapting the principles from cognitive architectures such as Soar, he aimed to improve LLMs’ memory management and task execution capabilities. Using the interactive Lovecraft-inspired game "Anchorhead," the developer created a Python wrapper that allows Claude to play by sending commands to and receiving outputs from the game interpreter. This setup transforms the gaming experience into a long-horizon task, pushing the boundaries of LLMs’ problem-solving abilities. This approach is significant for the AI/ML community as it presents a novel evaluation framework for LLMs, moving beyond typical tasks like coding or interactive chatbots. The experiments revealed limitations in memory handling; for example, when using a simple memory harness, Claude repeatedly wandered the game environment, failing to solve puzzles efficiently. Future developments involve refining memory structures to include domain-specific memories and implementing geographical awareness, which could further elevate the performance of LLMs in complex tasks. This ongoing research underscores the potential for cognitive science principles to shape next-generation AI architectures, demonstrating a practical avenue for enhancing agent intelligence in interactive settings.