George Konidaris
53 papers · 2009–2025 · 10 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (16) π Conference Polyglot (10)
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Conference Polyglot
(10)
πΊοΈ
Taxonomy Completionist
(16)
π§
Keyword Pioneer
π¬
Deep Specialist
(18)
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Triple Crown
π
Keyword Champion
(2)
π
Grand Slam
ποΈ
Keyword Collector
(206)
β‘
Prolific Year
(5)
π
Trend Setter
π
Century Club
(53)
π₯
Unstoppable
(12)
Conferences
ICML (12)
NIPS (12)
RSS (7)
ICLR (6)
IJCAI (6)
AAAI (4)
CORL (2)
JMLR (2)
AISTATS (1)
EMNLP (1)
Top co-authors
Research topics
Keywords
reinforcement learning
(14)
transfer learning
(5)
hierarchical reinforcement learning
(5)
deep reinforcement learning
(4)
continuous control
(4)
robot manipulation
(4)
value function
(4)
skill discovery
(3)
motion planning
(3)
option discovery
(3)
markov decision process
(3)
off-policy learning
(2)
online learning
(2)
imitation learning
(2)
demonstration learning
(2)
state representation
(2)
variational inference
(2)
temporal difference learning
(2)
hierarchical learning
(2)
active learning
(2)
Papers
Optimal Interactive Learning on the Job via Facility Location Planning
RSS 2025
Discovering Options That Minimize Average Planning Time
AAAI 2025
V-HOP: Visuo-Haptic 6D Object Pose Tracking
RSS 2025
Knowledge Retention in Continual Model-Based Reinforcement Learning
ICML 2025
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces
ICLR 2025
Language-guided Skill Learning with Temporal Variational Inference
ICML 2024
Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy
NIPS 2024
Model-based Reinforcement Learning for Parameterized Action Spaces
ICML 2024
EPO: Hierarchical LLM Agents with Environment Preference Optimization
EMNLP 2024
Meta-learning Parameterized Skills
ICML 2023
Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning
ICML 2023
RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agents
ICML 2023
Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
NIPS 2023
Synthesizing Navigation Abstractions for Planning with Portable Manipulation Skills
CORL 2023
Q-functionals for Value-Based Continuous Control
AAAI 2023
Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces
AISTATS 2023
Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs
ICLR 2023
Autonomous Learning of Object-Centric Abstractions for High-Level Planning
ICLR 2022
Optimistic Initialization for Exploration in Continuous Control
AAAI 2022
Model-based Lifelong Reinforcement Learning with Bayesian Exploration
NIPS 2022
Effects of Data Geometry in Early Deep Learning
NIPS 2022
Evaluation beyond Task Performance: Analyzing Concepts in AlphaZero in Hex
NIPS 2022
Robustly Learning Composable Options in Deep Reinforcement Learning
IJCAI 2021
Skill Discovery for Exploration and Planning using Deep Skill Graphs
ICML 2021
Learning Markov State Abstractions for Deep Reinforcement Learning
NIPS 2021
Efficient Black-Box Planning Using Macro-Actions with Focused Effects
IJCAI 2021
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms
JMLR 2021
Learning Portable Representations for High-Level Planning
ICML 2020
Exploration in Reinforcement Learning with Deep Covering Options
ICLR 2020
Simultaneously Learning Transferable Symbols and Language Groundings from Perceptual Data for Instruction Following
RSS 2020
Option Discovery using Deep Skill Chaining
ICLR 2020
Task Scoping for Efficient Planning in Open Worlds (Student Abstract)
AAAI 2020
Learning to Generalize Kinematic Models to Novel Objects
CORL 2019
Learning Multi-Level Hierarchies with Hindsight
ICLR 2019
Finding Options that Minimize Planning Time
ICML 2019
Discovering Options for Exploration by Minimizing Cover Time
ICML 2019
DeepMellow: Removing the Need for a Target Network in Deep Q-Learning
IJCAI 2019
Policy and Value Transfer in Lifelong Reinforcement Learning
ICML 2018
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes
NIPS 2017
Active Exploration for Learning Symbolic Representations
NIPS 2017
Bayesian Eigenobjects: A Unified Framework for 3D Robot Perception
RSS 2017
Constructing Abstraction Hierarchies Using a Skill-Symbol Loop
IJCAI 2016
Robot Motion Planning on a Chip
RSS 2016
Representing and Learning Complex Object Interactions
RSS 2016
Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations
IJCAI 2016
Symbol Acquisition for Probabilistic High-Level Planning
IJCAI 2015
Policy Search for Multi-Robot Coordination under Uncertainty
RSS 2015
Policy Evaluation Using the Ξ©-Return
NIPS 2015
Active Learning of Parameterized Skills
ICML 2014
Transfer in Reinforcement Learning via Shared Features
JMLR 2012
TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning
NIPS 2011
Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories
NIPS 2010
Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining
NIPS 2009