option discovery

Autonomous Option Invention for Continual Hierarchical Reinforcement Learning and Planning AAAI 2025 Discovering Options That Minimize Average Planning Time AAAI 2025 Representation-driven Option Discovery in Reinforcement Learning AAAI 2025 Reward-Respecting Subtasks for Model-Based Reinforcement Learning (Abstract Reprint) AAAI 2024 Unveiling Options with Neural Network Decomposition ICLR 2024 Deep Laplacian-based Options for Temporally-Extended Exploration ICML 2023 Creativity of AI: Automatic Symbolic Option Discovery for Facilitating Deep Reinforcement Learning AAAI 2022 Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs NeurIPS 2022 Discovery of Options via Meta-Learned Subgoals NeurIPS 2021 Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing ICML 2021 Exploration in Reinforcement Learning with Deep Covering Options ICLR 2020 Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills ICML 2020 Option Discovery in the Absence of Rewards with Manifold Analysis ICML 2020 Option Discovery using Deep Skill Chaining ICLR 2020 Options of Interest: Temporal Abstraction with Interest Functions AAAI 2020 Discovering Options for Exploration by Minimizing Cover Time ICML 2019 Finding Options that Minimize Planning Time ICML 2019 Successor Options: An Option Discovery Framework for Reinforcement Learning IJCAI 2019 The Termination Critic AISTATS 2019 An Inference-Based Policy Gradient Method for Learning Options ICML 2018 A Laplacian Framework for Option Discovery in Reinforcement Learning ICML 2017 DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations CoRL 2017 PAC-inspired Option Discovery in Lifelong Reinforcement Learning ICML 2014