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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

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Showing 401–425 of 514 papers

TitleStatusHype
Adaptive teachers for amortized samplersCode0
TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly DetectionCode0
ASCENT: Amplifying Power Side-Channel Resilience via Learning & Monte-Carlo Tree SearchCode0
Generalization and Exploration via Randomized Value FunctionsCode0
Personalized Algorithmic Recourse with Preference ElicitationCode0
Feature Interaction Aware Automated Data Representation TransformationCode0
EXPODE: EXploiting POlicy Discrepancy for Efficient Exploration in Multi-agent Reinforcement LearningCode0
GenPlan: Generative Sequence Models as Adaptive PlannersCode0
Exploring through Random Curiosity with General Value FunctionsCode0
Scalable Exploration via Ensemble++Code0
Randomized Value Functions via Multiplicative Normalizing FlowsCode0
GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal BabblingCode0
Exploratory State Representation LearningCode0
The MineRL 2019 Competition on Sample Efficient Reinforcement Learning using Human PriorsCode0
Goal-Reaching Policy Learning from Non-Expert Observations via Effective Subgoal GuidanceCode0
Go Beyond Imagination: Maximizing Episodic Reachability with World ModelsCode0
Receding Horizon CuriosityCode0
Sound Heuristic Search Value Iteration for Undiscounted POMDPs with Reachability ObjectivesCode0
Multi-Objective Hyperparameter Selection via Hypothesis Testing on Reliability GraphsCode0
Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse RewardsCode0
Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problemsCode0
Multirobot Coverage of Modular EnvironmentsCode0
Sparse Reward Exploration via Novelty Search and EmittersCode0
Count-Based Exploration in Feature Space for Reinforcement LearningCode0
Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision ProcessesCode0
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