Using relative novelty to identify useful temporal abstractions in reinforcement learning. - Özgür Simsek; Andrew G. Barto (ICML, 2004)

Towards Competence in Autonomous Agents. - Özgür Simsek (AAAI, 2005)

Identifying useful subgoals in reinforcement learning by local graph partitioning. - Özgür Simsek; Alicia P. Wolfe; Andrew G. Barto (ICML, 2005)

Decentralized Search in Networks Using Homophily and Degree Disparity. - Özgür Simsek; David D. Jensen (IJCAI, 2005)

Using relational knowledge discovery to prevent securities fraud. - Jennifer Neville; Özgür Simsek; David D. Jensen; John Komoroske; Kelly Palmer; Henry G. Goldberg (KDD, 2005)

Learning Skills in Reinforcement Learning Using Relative Novelty. - Özgür Simsek; Andrew G. Barto (SARA, 2005)

An intrinsic reward mechanism for efficient exploration. - Özgür Simsek; Andrew G. Barto (ICML, 2006)

Skill Characterization Based on Betweenness. - Özgür Simsek; Andrew G. Barto (NIPS, 2008)

Navigating networks by using homophily and degree. - Özgür Simsek; David D. Jensen (Proc. Natl. Acad. Sci. USA, 2008)

Workshop summary: Abstraction in reinforcement learning. - Özgür Simsek (ICML, 2009)

Linear decision rule as aspiration for simple decision heuristics. - Özgür Simsek (NIPS, 2013)

Learning From Small Samples: An Analysis of Simple Decision Heuristics. - Özgür Simsek; Marcus Buckmann (NIPS, 2015)

Why Most Decisions Are Easy in Tetris - And Perhaps in Other Sequential Decision Problems, As Well. - Özgür Simsek; Simón Algorta; Amit Kothiyal (ICML, 2016)

Decision Heuristics for Comparison: How Good Are They? - Marcus Buckmann; Özgür Simsek (IDM@NIPS, 2016)

Simple Regression Models. - Jan Malte Lichtenberg; Özgür Simsek (IDM@NIPS, 2016)

On Learning Decision Heuristics. - Özgür Simsek; Marcus Buckmann (IDM@NIPS, 2016)

Regularization in directable environments with application to Tetris. - Jan Malte Lichtenberg; Özgür Simsek (ICML, 2019)

The Game of Tetris in Machine Learning. - Simón Algorta; Özgür Simsek (CoRR, 2019)

Iterative Policy-Space Expansion in Reinforcement Learning. - Jan Malte Lichtenberg; Özgür Simsek (CoRR, 2019)

Fast and frugal heuristics for portfolio decisions with positive project interactions. - Ian N. Durbach; Simón Algorta; Dieudonné Kabongo Kantu; Konstantinos V. Katsikopoulos; Özgür Simsek (Decis. Support Syst., 2020)

RL4HCI: Reinforcement Learning for Humans, Computers, and Interaction. - Dorota Glowacka; Andrew Howes 001; Jussi P. P. Jokinen; Antti Oulasvirta; Özgür Simsek (CHI Extended Abstracts, 2021)

The Temporal Persistence of Generative Language Models in Sentiment Analysis. - Pablo Medina-Alias; Özgür Simsek (CLEF (Working Notes), 2023)

Explaining Reinforcement Learning with Shapley Values. - Daniel Beechey; Thomas M. S. Smith; Özgür Simsek (ICML, 2023)

Resource-Constrained Station-Keeping for Latex Balloons Using Reinforcement Learning. - Jack Saunders; Loïc Prenevost; Özgür Simsek; Alan Hunter 001; Wenbin Li 002 (IROS, 2023)

Creating Multi-Level Skill Hierarchies in Reinforcement Learning. - Joshua B. Evans; Özgür Simsek (NeurIPS, 2023)

Resource-Constrained Station-Keeping for Helium Balloons using Reinforcement Learning. - Jack Saunders; Loïc Prenevost; Özgür Simsek; Alan Hunter 001; Wenbin Li 002 (CoRR, 2023)

Colour versus Shape Goal Misgeneralization in Reinforcement Learning: A Case Study. - Karolis Ramanauskas; Özgür Simsek (CoRR, 2023)

Identifying Optimal Launch Sites of High-Altitude Latex-Balloons using Bayesian Optimisation for the Task of Station-Keeping. - Jack Saunders; Sajad Saeedi G.; Adam Hartshorne; Binbin Xu 001; Özgür Simsek; Alan Hunter 001; Wenbin Li 002 (IROS, 2024)

Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent. - Karolis Jucys; George Adamopoulos; Mehrab Hamidi; Stephanie Milani; Mohammad Reza Samsami; Artem Zholus; Sonia Joseph; Blake A. Richards; Irina Rish; Özgür Simsek (CoRR, 2024)

Curricula for Learning Robust Policies with Factored State Representations in Changing Environments. - Panayiotis Panayiotou 002; Özgür Simsek (CoRR, 2024)

Accelerating Task Generalisation with Multi-Level Hierarchical Options. - Thomas P. Cannon; Özgür Simsek (CoRR, 2024)

Hierarchical Orchestra of Policies. - Thomas P. Cannon; Özgür Simsek (CoRR, 2024)

Solving large-scale MEG/EEG source localisation and functional connectivity problems simultaneously using state-space models. - Jose Miguel Sanchez Bornot; Roberto C. Sotero; J. A. Scott Kelso; Özgür Simsek; Damien Coyle (NeuroImage, 2024)

Accelerating Task Generalisation with Multi-Level Skill Hierarchies. - Thomas P. Cannon; Özgür Simsek (ICLR, 2025)

A Theoretical Framework for Explaining Reinforcement Learning with Shapley Values. - Daniel Beechey; Thomas M. S. Smith; Özgür Simsek (CoRR, 2025)

Learning The Minimum Action Distance. - Lorenzo Steccanella; Joshua B. Evans; Özgür Simsek; Anders Jonsson 001 (CoRR, 2025)