Paper · arXiv 2308.01734
Ambient Adventures: Teaching ChatGPT on Developing Complex Stories
Zexin Chen, Eric Zhou, Kenneth Eaton, Xiangyu Peng, Mark Riedl
Large language models generate stories used to guide a robotic agent in imaginary play, which is evaluated in a simulated text adventure game.
Abstract
Imaginative play is an area of creativity that could allow robots to engage with the world around them in a much more personified way. Imaginary play can be seen as taking real objects and locations and using them as imaginary objects and locations in virtual scenarios. We adopted the story generation capability of large language models (LLMs) to obtain the stories used for imaginary play with human-written prompts. Those generated stories will be simplified and mapped into action sequences that can guide the agent in imaginary play. To evaluate whether the agent can successfully finish the imaginary play, we also designed a text adventure game to simulate a house as the playground for the agent to interact.