conftrace_

exploration policy

22 papers

Explore in graph

Co-occurring keywords

reinforcement learning (4352) regret bound (1926) meta-reinforcement learning (61) exploration strategy (96) state entropy (7) markov decision process (790) point cloud (1480) sample complexity (1169) policy gradient (520) scene understanding (825)

Papers

InfiGUI-G1: Advancing GUI Grounding with Adaptive Exploration Policy Optimization AAAI 2026
GLEAM: Learning Generalizable Exploration Policy for Active Mapping in Complex 3D Indoor Scene ICCV 2025
A Category Agnostic Model for Visual Rearrangment CVPR 2024
Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL NIPS 2024
Jump-Start Reinforcement Learning ICML 2023
Maximum State Entropy Exploration using Predecessor and Successor Representations NIPS 2023
3D-Aware Object Goal Navigation via Simultaneous Exploration and Identification CVPR 2023
Safe Exploration for Efficient Policy Evaluation and Comparison ICML 2022
Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning AAAI 2021
Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate AAAI 2021
Meta-Reinforcement Learning by Tracking Task Non-stationarity IJCAI 2021
MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration ICML 2021
Meta-Learning Effective Exploration Strategies for Contextual Bandits AAAI 2021
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits NIPS 2020
Private Reinforcement Learning with PAC and Regret Guarantees ICML 2020
Learning Active Task-Oriented Exploration Policies for Bridging the Sim-to-Real Gap RSS 2020
Provably Efficient Q-Learning with Low Switching Cost NIPS 2019
Learning Transferable Graph Exploration NIPS 2019
Provably efficient RL with Rich Observations via Latent State Decoding ICML 2019
Learning to Explore via Meta-Policy Gradient ICML 2018
Learning Unknown Markov Decision Processes: A Thompson Sampling Approach NIPS 2017
Cost-Sensitive Exploration in Bayesian Reinforcement Learning NIPS 2012