SOTAVerified

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 181190 of 514 papers

TitleStatusHype
Reinforcement learning informed evolutionary search for autonomous systems testing0
Bag of Policies for Distributional Deep Exploration0
Towards A Unified Agent with Foundation Models0
LISSNAS: Locality-based Iterative Search Space Shrinkage for Neural Architecture Search0
Approximate information for efficient exploration-exploitation strategies0
Improving Protein Optimization with Smoothed Fitness LandscapesCode1
Maximum State Entropy Exploration using Predecessor and Successor Representations0
DISCO-10M: A Large-Scale Music Dataset0
Inferring Hierarchical Structure in Multi-Room Maze Environments0
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP0
Show:102550
← PrevPage 19 of 52Next →

No leaderboard results yet.