Creativity, Compositionality, and Common Sense in Human Goal Generation


Inspired by notions of intrinsic motivation (Schmidhuber, 2010) and play as proposing and solving arbitrary problems (Chu & Schulz, 2020) we report initial progress toward computational modeling of playful goal generation. We create an embodied, 3D environment resembling a child’s bedroom, and ask study participants to play in the environment and then create a scorable game. We propose to model games using a domain-specific language, which represents each game as a computer program. These programs act as reward-generating functions, mapping states visited by an agent as they play a game to the score they should receive. We then analyze our corpus of program representations to highlight four key aspects of human games that would contribute to constructing effective computational models of game generation: creativity, compositionality, common sense, and context sensitivity.

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, CogSci 2022