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Iirc, the best approaches for this nowadays are machine learning based. Otherwise, you probably want to do an exploration step first, and bake in the environmen
by ViscountPenguin 1y ago
Iirc, the best approaches for this nowadays are machine learning based. Otherwise, you probably want to do an exploration step first, and bake in the environment.
- gradstudent 1y agoML methods are poor pathfinders. I'm unaware of any pathfinding problem where SOTA is not dominated by state-space search.
- ViscountPenguin 1y agoI can't find any benchmarks, but here's an example of the sort of approach I was talking about: https://www.researchgate.net/publication/355761412_Path_planning_in_an_unknown_environment_based_on_deep_reinforcement_learning_with_prior_knowledge https://www.researchgate.net/publication/355761412_Path_plan... GOFAI techniques are: A) Usually unable to incorporate posteri knowledge of the environments they're working on. And B) Often entirely infeasible to adapt to take exploration costs into account. I've heard of some GOFAI techniques for optimal unbiased pathfinding in unknown environments using optimal transport theory and the like. But unbiased methods are obviously going to lose out in real environments.