← Authors

George Konidaris

53 papers · 2009–2025 · 10 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (16) 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (10) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (10) πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer πŸ”¬ Deep Specialist (18) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (206) ⚑ Prolific Year (5) πŸ“ˆ Trend Setter πŸ’Ž Century Club (53) πŸ”₯ 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

Haotian Fu (7) Michael Littman (7) Omer Gottesman (7) Akhil Bagaria (7) Stefanie Tellex (5) Cameron Allen (4) Yuu Jinnai (4) Steven James (3) Finale Doshi-velez (3) Scott Niekum (3)

Research topics

Reinforcement Learning (1) Robotics (1)

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