David Abel
22 papers · 2016–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π§ Keyword Pioneer π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (11) π Academic Marathon (9)
π
Interdisciplinary Bridge
π
Conference Polyglot
(7)
π§
Keyword Pioneer
π
Keyword Champion
(2)
π
Grand Slam
ποΈ
Keyword Collector
(78)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Century Club
(22)
π₯
Unstoppable
(8)
π
Trend Setter
β
The Questioner
Conferences
ICML (10)
AAAI (4)
ICLR (2)
IJCAI (2)
NIPS (2)
AISTATS (1)
JMLR (1)
Top co-authors
Keywords
reinforcement learning
(9)
state abstraction
(6)
value function
(4)
lifelong reinforcement learning
(3)
markov decision process
(3)
pac learning
(2)
markov reward
(2)
option discovery
(2)
hierarchical abstraction
(2)
transfer learning
(2)
optimal policy
(2)
information theory
(2)
lifelong learning
(2)
task specification
(2)
function approximation
(1)
hierarchical learning
(1)
continual learning
(1)
hierarchical planning
(1)
information bottleneck
(1)
deep reinforcement learning
(1)
Papers
Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning
ICLR 2025
Optimizing Return Distributions with Distributional Dynamic Programming
JMLR 2025
General agents need world models
ICML 2025
A Black Swan Hypothesis: The Role of Human Irrationality in AI Safety
ICLR 2025
Pragmatic Feature Preferences: Learning Reward-Relevant Preferences from Human Input
ICML 2024
Settling the Reward Hypothesis
ICML 2023
A Definition of Continual Reinforcement Learning
NIPS 2023
On the Expressivity of Markov Reward (Extended Abstract)
IJCAI 2022
On the Expressivity of Markov Reward
NIPS 2021
Lipschitz Lifelong Reinforcement Learning
AAAI 2021
Revisiting Pengβs Q($Ξ»$) for Modern Reinforcement Learning
ICML 2021
What can I do here? A Theory of Affordances in Reinforcement Learning
ICML 2020
Value Preserving State-Action Abstractions
AISTATS 2020
People Do Not Just Plan,They Plan to Plan
AAAI 2020
The Expected-Length Model of Options
IJCAI 2019
A Theory of State Abstraction for Reinforcement Learning
AAAI 2019
State Abstraction as Compression in Apprenticeship Learning
AAAI 2019
Finding Options that Minimize Planning Time
ICML 2019
Discovering Options for Exploration by Minimizing Cover Time
ICML 2019
Policy and Value Transfer in Lifelong Reinforcement Learning
ICML 2018
State Abstractions for Lifelong Reinforcement Learning
ICML 2018
Near Optimal Behavior via Approximate State Abstraction
ICML 2016