SOTAVerified|Agents Browse Leaderboard About

Efficient Exploration

Efficient Exploration is one of the main obstacles in scaling up modern deep reinforcement learning algorithms. The main challenge in Efficient Exploration is the balance between exploiting current estimates, and gaining information about poorly understood states and actions.

Source: Randomized Value Functions via Multiplicative Normalizing Flows

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 441–450 of 514 papers

Title	Date	Tasks	Status
Noisy Networks for Exploration	Jun 30, 2017	Atari GamesDeep Reinforcement Learning	CodeCode Available
Angrier Birds: Bayesian reinforcement learning	Jan 6, 2016	Efficient ExplorationQ-Learning	CodeCode Available
Reward-Centered ReST-MCTS: A Robust Decision-Making Framework for Robotic Manipulation in High Uncertainty Environments	Mar 7, 2025	Decision MakingEfficient Exploration	CodeCode Available
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables	Mar 19, 2019	Deep Reinforcement LearningEfficient Exploration	CodeCode Available
Nonlinear model reduction for slow-fast stochastic systems near unknown invariant manifolds	Apr 5, 2021	Efficient Exploration	CodeCode Available
A New Bandit Setting Balancing Information from State Evolution and Corrupted Context	Nov 16, 2020	Decision MakingEfficient Exploration	CodeCode Available
Information-Directed Exploration for Deep Reinforcement Learning	Dec 18, 2018	Atari GamesDeep Reinforcement Learning	CodeCode Available
IN-RIL: Interleaved Reinforcement and Imitation Learning for Policy Fine-Tuning	May 15, 2025	Efficient ExplorationImitation Learning	CodeCode Available
Instance Temperature Knowledge Distillation	Jun 27, 2024	Decision MakingEfficient Exploration	CodeCode Available
Consensus-based adaptive sampling and approximation for high-dimensional energy landscapes	Nov 8, 2023	Efficient Exploration	CodeCode Available

Show:10 25 50

← PrevPage 45 of 52Next →

No leaderboard results yet.