@inproceedings{e3e6ab131add45ad933417c5581f1091,
title = "Using relative novelty to identify useful temporal abstractions in reinforcement learning",
abstract = "We present a new method for automatically creating useful temporal abstractions in reinforcement learning. We argue that states that allow the agent to transition to a different region of the state space are useful subgoals, and propose a method for identifying them using the concept of relative novelty. When such a state is identified, a temporally-extended activity (e.g., an option) is generated that takes the agent efficiently to this state. We illustrate the utility of the method in a number of tasks.",
author = "{\"O}zg{\"u}r {\c S}im{\c s}ek and Barto, {Andrew G.}",
year = "2004",
month = jan,
day = "1",
language = "English",
volume = "69",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
editor = "Brodley, {Carla E.}",
booktitle = "Proceedings of the Twenty-first International Conference on Machine Learning (ICML 2004): Banff, Alberta, Canada, July 4-8, 2004",
address = "USA United States",
}