5 papers
In-Context Planning with Latent Temporal Abstractions
Baiting Luo, Yunuo Zhang, Nathaniel S. Keplinger +3
Planning-based reinforcement learning for continuous control is bottlenecked by two practical issues: planning at primitive time scales leads to prohibitive branching and long hori…
Online Decision-Making Under Uncertainty for Vehicle-to-Building Systems
Rishav Sen, Yunuo Zhang, Fangqi Liu +5
Vehicle-to-building (V2B) systems integrate physical infrastructures, such as smart buildings and electric vehicles (EVs) connected to chargers at the building, with digital contro…
ESCORT: Efficient Stein-variational and Sliced Consistency-Optimized Temporal Belief Representation for POMDPs
Yunuo Zhang, Baiting Luo, Ayan Mukhopadhyay +2
In Partially Observable Markov Decision Processes (POMDPs), maintaining and updating belief distributions over possible underlying states provides a principled way to summarize act…
Observation Adaptation via Annealed Importance Resampling for Partially Observable Markov Decision Processes
Yunuo Zhang, Baiting Luo, Ayan Mukhopadhyay +1
Partially observable Markov decision processes (POMDPs) are a general mathematical model for sequential decision-making in stochastic environments under state uncertainty. POMDPs a…
NS-Gym: Open-Source Simulation Environments and Benchmarks for Non-Stationary Markov Decision Processes
Nathaniel S. Keplinger, Baiting Luo, Iliyas Bektas +5
In many real-world applications, agents must make sequential decisions in environments where conditions are subject to change due to various exogenous factors. These non-stationary…