I don’t think gpt2 is useful in the way described, its just spitting out nonsense. Text adventures are hard because you have structured data (eg. a scene with

I don’t think gpt2 is useful in the way described, its just spitting out nonsense. Text adventures are hard because you have structured data (eg. a scene with N objects in it), but you want to generate a text fragment dynamically as the state of those objects changes. It meaningless to just randomly generate text fragments; you have to parse the input of free text (hard, eg. turn off the light; yes it is hard when its free text), update the state of the scene (easy, eg. set light level to low)... ... and then return a new text snippet that describes the scene (extremely hard, unless you constrain the state transitions to a finite hardcoded set). so, like, tldr, you could do something really cool here, to use a language model to describe a scene over a continuous range of states using a finite set of samples and that would be amazing! ...but, I dont really see seeding a text fragment from a set of words being a particularly interesting addition to the field.