1 code implementation • 5 Dec 2023 • Karolis Ramanauskas, Özgür Şimşek
We explore colour versus shape goal misgeneralization originally demonstrated by Di Langosco et al. (2022) in the Procgen Maze environment, where, given an ambiguous choice, the agents seem to prefer generalization based on colour rather than shape.
1 code implementation • NeurIPS 2023 • Joshua B. Evans, Özgür Şimşek
What is a useful skill hierarchy for an autonomous agent?
1 code implementation • 9 Jun 2023 • Daniel Beechey, Thomas M. S. Smith, Özgür Şimşek
For reinforcement learning systems to be widely adopted, their users must understand and trust them.
no code implementations • 2 Mar 2023 • Jack Saunders, Loïc Prenevost, Özgür Şimşek, Alan Hunter, Wenbin Li
Very recently, reinforcement learning has been proposed as a control scheme to maintain the balloon in the region of a fixed location, facilitated through diverse opposing wind-fields at different altitudes.
no code implementations • 5 Dec 2019 • Jan Malte Lichtenberg, Özgür Şimşek
Humans and animals solve a difficult problem much more easily when they are presented with a sequence of problems that starts simple and slowly increases in difficulty.
1 code implementation • 5 May 2019 • Simón Algorta, Özgür Şimşek
The game of Tetris is an important benchmark for research in artificial intelligence and machine learning.
no code implementations • NeurIPS 2015 • Özgür Şimşek, Marcus Buckmann
Simple decision heuristics are models of human and animal behavior that use few pieces of information---perhaps only a single piece of information---and integrate the pieces in simple ways, for example, by considering them sequentially, one at a time, or by giving them equal weight.
no code implementations • NeurIPS 2013 • Özgür Şimşek
Many attempts to understand the success of simple decision heuristics have examined heuristics as an approximation to a linear decision rule.
no code implementations • NeurIPS 2008 • Özgür Şimşek, Andrew G. Barto
We present a characterization of a useful class of skills based on a graphical representation of an agent's interaction with its environment.