no code implementations • 22 Jul 2023 • Hai Nguyen, Sammie Katt, Yuchen Xiao, Christopher Amato
Bayesian reinforcement learning (BRL), thanks to its sample efficiency and ability to exploit prior knowledge, is uniquely positioned as such a solution method.
no code implementations • 17 Feb 2022 • Sammie Katt, Hai Nguyen, Frans A. Oliehoek, Christopher Amato
Under this parameterization, in contrast to previous work, the belief over the state and dynamics is a more scalable inference problem.
no code implementations • 24 Mar 2020 • Pushyami Kaveti, Sammie Katt, Hanumant Singh
In this paper we present a method to synthesize a refocused image of the static background in the presence of dynamic objects that uses a light-field acquired with a linear camera array.
no code implementations • 14 Nov 2018 • Sammie Katt, Frans Oliehoek, Christopher Amato
Bayesian approaches provide a principled solution to the exploration-exploitation trade-off in Reinforcement Learning.
no code implementations • ICML 2017 • Sammie Katt, Frans A. Oliehoek, Christopher Amato
The POMDP is a powerful framework for reasoning under outcome and information uncertainty, but constructing an accurate POMDP model is difficult.