Accelerating Value Iteration with Anchoring

Authors: Jongmin Lee, Ernest Ryu

NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical Our work focuses on the theoretical aspects of reinforcement learning. There are no negative social impacts that we anticipate from our theoretical results.
Researcher Affiliation Academia Jongmin Lee1 Ernest K. Ryu1,2 1Department of Mathematical Science, Seoul National University 2Interdisciplinary Program in Artificial Intelligence, Seoul National University
Pseudocode No The paper describes algorithms (Anc-VI, Apx-Anc-VI, GS-Anc-VI) through mathematical equations and definitions but does not include any explicitly labeled 'Pseudocode' or 'Algorithm' blocks.
Open Source Code No The paper is theoretical and does not mention providing any open-source code for the methodology described.
Open Datasets No The paper is theoretical and does not describe any experimental setup involving datasets or their public availability.
Dataset Splits No The paper is theoretical and does not describe dataset splits for validation purposes. There are no experiments conducted with data.
Hardware Specification No The paper is theoretical and does not mention any hardware specifications used for experiments.
Software Dependencies No The paper is theoretical and does not mention any software dependencies for experimental setup.
Experiment Setup No The paper is theoretical and does not describe any experimental setup, hyperparameters, or training configurations.