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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

Showing 5160 of 514 papers

TitleStatusHype
Adversarially Guided Actor-CriticCode1
BeBold: Exploration Beyond the Boundary of Explored RegionsCode1
Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* NeighborhoodCode1
Latent World Models For Intrinsically Motivated ExplorationCode1
Novelty Search in Representational Space for Sample Efficient ExplorationCode1
Occupancy Anticipation for Efficient Exploration and NavigationCode1
DeepDrummer : Generating Drum Loops using Deep Learning and a Human in the LoopCode1
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement LearningCode1
See, Hear, Explore: Curiosity via Audio-Visual AssociationCode1
MetaCURE: Meta Reinforcement Learning with Empowerment-Driven ExplorationCode1
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