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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 91100 of 514 papers

TitleStatusHype
Bayesian optimization of distributed neurodynamical controller models for spatial navigation0
Adaptformer: Sequence models as adaptive iterative planners0
Data-Efficient Exploration with Self Play for Atari0
Bayesian optimisation of large-scale photonic reservoir computers0
A Natural Extension To Online Algorithms For Hybrid RL With Limited Coverage0
CURO: Curriculum Learning for Relative Overgeneralization0
A Community Based Algorithm for Large Scale Web Service Composition0
Deep Active Ensemble Sampling For Image Classification0
Discovering Context Specific Causal Relationships0
Distilling Realizable Students from Unrealizable Teachers0
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