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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 376–400 of 514 papers

TitleStatusHype
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable—0
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model—0
Bridging Text and Crystal Structures: Literature-driven Contrastive Learning for Materials Science—0
Credit Assignment and Efficient Exploration based on Influence Scope in Multi-agent Reinforcement Learning—0
Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning—0
Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation—0
CURO: Curriculum Learning for Relative Overgeneralization—0
Data-Efficient Exploration with Self Play for Atari—0
Deep Active Ensemble Sampling For Image Classification—0
Deep density networks and uncertainty in recommender systems—0
Deep exploration by novelty-pursuit with maximum state entropy—0
Deep Exploration via Randomized Value Functions—0
DEEPGONET: Multi-label Prediction of GO Annotation for Protein from Sequence Using Cascaded Convolutional and Recurrent Network—0
Deep Neural Linear Bandits: Overcoming Catastrophic Forgetting through Likelihood Matching—0
Design of Convolutional Extreme Learning Machines for Vision-Based Navigation Around Small Bodies—0
Deterministic Sequencing of Exploration and Exploitation for Reinforcement Learning—0
Differentially Evolving Memory Ensembles: Pareto Optimization based on Computational Intelligence for Embedded Memories on a System Level—0
DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models—0
Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning—0
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous and Instruction-guided Driving—0
Diffusion Models Meet Contextual Bandits with Large Action Spaces—0
Directed Exploration for Reinforcement Learning—0
Directed Exploration in PAC Model-Free Reinforcement Learning—0
DISCO-10M: A Large-Scale Music Dataset—0
Discovering Context Specific Causal Relationships—0
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