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 381–390 of 514 papers

Title	Date	Tasks	Status	Hype
Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies	Jan 1, 2020	Efficient ExplorationMeta Reinforcement Learning	CodeCode Available	1
Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning	Dec 23, 2019	Efficient Explorationreinforcement-learning	CodeCode Available	0
Recruitment-imitation Mechanism for Evolutionary Reinforcement Learning	Dec 13, 2019	continuous-controlContinuous Control	—Unverified	0
Provably Efficient Exploration in Policy Optimization	Dec 12, 2019	Efficient ExplorationReinforcement Learning	—Unverified	0
Explicit Planning for Efficient Exploration in Reinforcement Learning	Dec 1, 2019	Efficient Explorationreinforcement-learning	—Unverified	0
Better Exploration with Optimistic Actor Critic	Dec 1, 2019	continuous-controlContinuous Control	CodeCode Available	0
Comprehensive decision-strategy space exploration for efficient territorial planning strategies	Nov 26, 2019	Efficient Exploration	—Unverified	0
Scaling active inference	Nov 24, 2019	Efficient ExplorationReinforcement Learning	—Unverified	0
Bayesian Curiosity for Efficient Exploration in Reinforcement Learning	Nov 20, 2019	Efficient Explorationreinforcement-learning	CodeCode Available	0
Implicit Generative Modeling for Efficient Exploration	Nov 19, 2019	Efficient ExplorationFuture prediction	—Unverified	0

Show:10 25 50

← PrevPage 39 of 52Next →

No leaderboard results yet.