Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning | Paper Citation Record

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This paper cites Playing Atari with Deep Reinforcement Learning.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Playing Atari with Deep Reinforcement Learning

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This paper cites Human-level control through deep reinforcement learning.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Human-level control through deep reinforcement learning

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Mastering the game of go with deep neural networks and tree search

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Mastering the game of go without human knowledge

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This paper cites Dota 2 with Large Scale Deep Reinforcement Learning.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Dota 2 with Large Scale Deep Reinforcement Learning

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This paper cites Alphastar: An evolutionary computation perspective.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Alphastar: An evolutionary computation perspective

Reference 6

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Observation 8e6e462a-9ed2-46c4-b9da-9a4f92db2151 · outbound

This paper cites Unifying count-based exploration and intrinsic motivation.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Unifying count-based exploration and intrinsic motivation

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This paper cites Curiosity-driven exploration by self- supervised prediction.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Curiosity-driven exploration by self- supervised prediction

Reference 8

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This paper cites Count-based exploration with neural density models.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Count-based exploration with neural density models

Reference 9

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Observation 64bacd47-a6d9-4b9a-9f86-fb6817e829a8 · outbound

This paper cites Exploration by Random Network Distillation.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Exploration by Random Network Distillation

Reference 10

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This paper cites Count-based exploration with the successor representation.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Count-based exploration with the successor representation

Reference 11

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This paper cites Self-supervised exploration via disagreement.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Self-supervised exploration via disagreement

Reference 12

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Observation 47bcd4c3-323b-46c9-b3f5-4db9e47f67be · outbound

This paper cites Using confidence bounds for exploitation-exploration trade-offs.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Using confidence bounds for exploitation-exploration trade-offs

Reference 13

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This paper cites Minimax regret bounds for reinforcement learning.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Minimax regret bounds for reinforcement learning

Reference 14

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Observation f7dfa20d-b28b-466d-812e-1002fb601f6c · outbound

This paper cites Is q-learning provably efficient? Advances in neural information processing systems, 31, 2018.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Is q-learning provably efficient? Advances in neural information processing systems, 31, 2018

Reference 15

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This paper cites Reinforcement learning in feature space: Matrix bandit, kernels, and regret bound.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Reinforcement learning in feature space: Matrix bandit, kernels, and regret bound

Reference 16

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This paper cites Provably efficient reinforcement learning with linear function approximation.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Provably efficient reinforcement learning with linear function approximation

Reference 17

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This paper cites Decoupling exploration and exploitation in reinforcement learning.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Decoupling exploration and exploitation in reinforcement learning

Reference 18

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This paper cites Decoupled Exploration and Exploitation Policies for Sample-Efficient Reinforcement Learning.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Decoupled Exploration and Exploitation Policies for Sample-Efficient Reinforcement Learning

Reference 19

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This paper cites A markovian decision process.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning A markovian decision process

Reference 20

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Q-learning

Reference 21

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This paper cites Sample-optimal parametric q-learning using linearly additive features.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Sample-optimal parametric q-learning using linearly additive features

Reference 22

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This paper cites Addressing function approximation error in actor-critic methods.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Addressing function approximation error in actor-critic methods

Reference 23

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This paper cites D4RL: Datasets for Deep Data-Driven Reinforcement Learning.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 24

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This paper cites Mujoco: A physics engine for model-based control.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Mujoco: A physics engine for model-based control

Reference 25

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This paper cites On the likelihood that one unknown probability exceeds another in view of the evidence of two samples.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning On the likelihood that one unknown probability exceeds another in view of the evidence of two samples

Reference 26

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This paper cites Intrinsic motivation systems for autonomous mental development.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Intrinsic motivation systems for autonomous mental development

Reference 27

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning # exploration: A study of count-based exploration for deep reinforcement learning

Reference 28

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning DORA The Explorer: Directed Outreaching Reinforcement Action-Selection

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Go-Explore: a New Approach for Hard-Exploration Problems

Reference 30

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Bayesian reinforcement learning: A survey

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Noisy Networks for Exploration

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Deep exploration via bootstrapped dqn

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning The option-critic architecture

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Temporally-Extended {\epsilon}-Greedy Exploration

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Redeeming intrinsic rewards via constrained optimization

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Decoupling exploration and exploitation for meta- reinforcement learning without sacrifices

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Improved algorithms for linear stochastic bandits

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning healthy reward

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning And further, X k∈I ˆV k 1 (sk

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning By recursively applying Equation

Reference 56

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Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning Hence, the total regret is given by: KX k=1 ˆV k 1 (sk

Reference 58

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Observation 21551000-93d4-4bbc-881b-c4214708596e · outbound

This paper cites And equivalently, we conclude that our algorithm obtains ϵ-optimal policy with ˜O( d3H 4 ϵ2 ) samples with probability at least 1 − δ.

Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning And equivalently, we conclude that our algorithm obtains ϵ-optimal policy with ˜O( d3H 4 ϵ2 ) samples with probability at least 1 − δ

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:15:10.425577Z

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