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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 151–200 of 514 papers

TitleStatusHype
Fractional Langevin Monte Carlo: Exploring Lévy Driven Stochastic Differential Equations for Markov Chain Monte Carlo—0
GAN-based Intrinsic Exploration For Sample Efficient Reinforcement Learning—0
Guided Exploration for Efficient Relational Model Learning—0
Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization—0
Efficient Exploration using Model-Based Quality-Diversity with Gradients—0
Finedeep: Mitigating Sparse Activation in Dense LLMs via Multi-Layer Fine-Grained Experts—0
Efficient Exploration Using Extra Safety Budget in Constrained Policy Optimization—0
Efficient Exploration through Intrinsic Motivation Learning for Unsupervised Subgoal Discovery in Model-Free Hierarchical Reinforcement Learning—0
Autonomous synthesis of metastable materials—0
Efficient exploration with Double Uncertain Value Networks—0
Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards—0
Efficient gPC-based quantification of probabilistic robustness for systems in neuroscience—0
Context-Dependent Upper-Confidence Bounds for Directed Exploration—0
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation—0
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable—0
FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching—0
FIT-SLAM -- Fisher Information and Traversability estimation-based Active SLAM for exploration in 3D environments—0
Co-NavGPT: Multi-Robot Cooperative Visual Semantic Navigation Using Vision Language Models—0
Efficient Pose and Cell Segmentation using Column Generation—0
Reinforcement Learning for Causal Discovery without Acyclicity Constraints—0
Efficient Reinforcement Learning in Deterministic Systems with Value Function Generalization—0
Efficient Robotic Object Search via HIEM: Hierarchical Policy Learning with Intrinsic-Extrinsic Modeling—0
Embodied Agents for Efficient Exploration and Smart Scene Description—0
Emotion-Agent: Unsupervised Deep Reinforcement Learning with Distribution-Prototype Reward for Continuous Emotional EEG Analysis—0
Efficient exploration of zero-sum stochastic games—0
Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning—0
Entropic Risk-Sensitive Reinforcement Learning: A Meta Regret Framework with Function Approximation—0
Entropy-guided sequence weighting for efficient exploration in RL-based LLM fine-tuning—0
Feature Engineering for Predictive Modeling using Reinforcement Learning—0
ESC: Exploration with Soft Commonsense Constraints for Zero-shot Object Navigation—0
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization—0
ActiveGAMER: Active GAussian Mapping through Efficient Rendering—0
Evolutionary Reinforcement Learning via Cooperative Coevolution—0
Finding Waldo: Towards Efficient Exploration of NeRF Scene Spaces—0
Explicit Planning for Efficient Exploration in Reinforcement Learning—0
Explicit Recall for Efficient Exploration—0
Exploration Bonus for Regret Minimization in Undiscounted Discrete and Continuous Markov Decision Processes—0
Exploration by Distributional Reinforcement Learning—0
Exploration by Learning Diverse Skills through Successor State Measures—0
Exploration by Uncertainty in Reward Space—0
Efficient Exploration of Image Classifier Failures with Bayesian Optimization and Text-to-Image Models—0
Exploration in Model-based Reinforcement Learning with Randomized Reward—0
Exploration of the search space of Gaussian graphical models for paired data—0
Exploration via Epistemic Value Estimation—0
Data-Efficient Exploration with Self Play for Atari—0
Exploratory Diffusion Model for Unsupervised Reinforcement Learning—0
Deep Active Ensemble Sampling For Image Classification—0
Explore until Confident: Efficient Exploration for Embodied Question Answering—0
A Straightforward Gradient-Based Approach for High-Tc Superconductor Design: Leveraging Domain Knowledge via Adaptive Constraints—0
Computing low-thrust transfers in the asteroid belt, a comparison between astrodynamical manipulations and a machine learning approach—0
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