From the 1 of 9 linked papers with an AI index.
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The Surprising Difficulty of Search in Model-Based Reinforcement Learning
Wei-Di Chang, Mikael Henaff, Brandon Amos +2
This paper investigates search in model-based reinforcement learning (RL). Conventional wisdom holds that long-term predictions and compounding errors are the primary obstacles for…
Contractive Diffusion Policies: Robust Action Diffusion via Contractive Score-Based Sampling with Differential Equations
Amin Abyaneh, Charlotte Morissette, Mohamad H. Danesh +4
Diffusion policies have emerged as powerful generative models for offline policy learning, whose sampling process can be rigorously characterized by a score function guiding a stoc…
Learning Heuristics for Transit Network Design and Improvement with Deep Reinforcement Learning
Andrew Holliday, Ahmed El-Geneidy, Gregory Dudek
Planning a network of public transit routes is a challenging optimization problem. Metaheuristic algorithms search through the space of possible transit networks by applying heuris…