Yes. There is a whole sector of algorithm design called online algorithms dedicated to studying algorithms that must make decisions without complete information. A common analysis technique proves the "competitive ratio" of an algorithm by analyzing its worst case performance against an adversary. In fact, this article was the analysis of one particular online problem. For a simple introduction, you can check out "the ski rental problem." More complex applications include things like task scheduling and gradient descent.

Adjacent to this topic is algorithms for two-player games, like minimax, which depend on imagining an adversary that plays perfect counter moves.

In a similar vein, in ML, there is a model called generative adversarial networks (GANs) in which 2 networks (a generator and discriminator) play a minimax game against each other, improving the capability of both models at once.