Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes | Paper Citation Record

Observation f3ce5166-102e-49cb-b77e-86b7d2e3b02e · outbound

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

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Human-level control through deep reinforcement learning,

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Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Continuous control with deep reinforcement learning

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This paper cites Trust Region Policy Optimization.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Trust Region Policy Optimization

Reference 3

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This paper cites Deep Reinforcement Learning framework for Autonomous Driving.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Deep Reinforcement Learning framework for Autonomous Driving

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This paper cites Continuous mdp homomorphisms and homomorphic policy gradient,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Continuous mdp homomorphisms and homomorphic policy gradient,

Reference 5

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This paper cites TD-MPC2: Scalable, Robust World Models for Continuous Control.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes TD-MPC2: Scalable, Robust World Models for Continuous Control

Reference 6

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This paper cites Movie: Visual model-based policy adaptation for view generalization,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Movie: Visual model-based policy adaptation for view generalization,

Reference 7

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This paper cites Making better decision by directly planning in continuous control,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Making better decision by directly planning in continuous control,

Reference 8

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Observation efd40ed2-e94b-4ee3-8e81-250cc28bf14c · outbound

This paper cites Hierarchical advantage for reinforcement learning in parameterized action space,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Hierarchical advantage for reinforcement learning in parameterized action space,

Reference 9

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This paper cites Deep Reinforcement Learning in Parameterized Action Space.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Deep Reinforcement Learning in Parameterized Action Space

Reference 10

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This paper cites Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces

Reference 11

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This paper cites Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space

Reference 12

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Observation 214518cb-6f71-4875-bb3e-b8c8c8a3b67a · outbound

This paper cites Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space

Reference 13

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This paper cites HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation

Reference 14

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This paper cites Reinforcement learning with parameterized actions,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Reinforcement learning with parameterized actions,

Reference 15

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Observation 35cbf09d-f9b8-4de6-8456-c4e8ee3bdedf · outbound

This paper cites Dream to Control: Learning Behaviors by Latent Imagination.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Dream to Control: Learning Behaviors by Latent Imagination

Reference 16

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This paper cites Mastering Atari with Discrete World Models.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Mastering Atari with Discrete World Models

Reference 17

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This paper cites Privileged Sensing Scaffolds Reinforcement Learning.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Privileged Sensing Scaffolds Reinforcement Learning

Reference 18

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Observation 34d92f07-a7cd-49b7-9bb0-2ca85dc350f9 · outbound

This paper cites Model-based Reinforcement Learning for Parameterized Action Spaces.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Model-based Reinforcement Learning for Parameterized Action Spaces

Reference 19

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This paper cites The Benefits of Model-Based Generalization in Reinforcement Learning.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes The Benefits of Model-Based Generalization in Reinforcement Learning

Reference 20

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This paper cites Diminishing return of value expansion methods in model-based reinforcement learning,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Diminishing return of value expansion methods in model-based reinforcement learning,

Reference 21

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Observation 43c3c435-2a7c-4e9e-a36b-c1bef140e093 · outbound

This paper cites Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning

Reference 22

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Observation 55f67307-798f-4012-bfd5-64cbd6767d41 · outbound

This paper cites DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing

Reference 23

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Observation 57fc4af9-3968-4d15-aff1-64006f9c2c8b · outbound

This paper cites Multi-Pass Q-Networks for Deep Reinforcement Learning with Parameterised Action Spaces.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Multi-Pass Q-Networks for Deep Reinforcement Learning with Parameterised Action Spaces

Reference 24

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This paper cites Learning insertion primitives with discrete-continuous hybrid action space for robotic assembly tasks,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Learning insertion primitives with discrete-continuous hybrid action space for robotic assembly tasks,

Reference 25

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This paper cites Lipschitz continuity in model- based reinforcement learning,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Lipschitz continuity in model- based reinforcement learning,

Reference 26

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This paper cites Markov processes over denumerable products of spaces, describing large systems of automata,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Markov processes over denumerable products of spaces, describing large systems of automata,

Reference 27

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This paper cites Explaining and Harnessing Adversarial Examples.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Explaining and Harnessing Adversarial Examples

Reference 28

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This paper cites A mathematical theory of communication,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes A mathematical theory of communication,

Reference 29

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This paper cites The im algorithm: a variational approach to information maximization,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes The im algorithm: a variational approach to information maximization,

Reference 30

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This paper cites Learning-based model predictive control for markov decision processes,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Learning-based model predictive control for markov decision processes,

Reference 31

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Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Optimization of computer simulation models with rare events,

Reference 32

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This paper cites Plan to predict: Learning an uncertainty-foreseeing model for model-based reinforce- ment learning,.

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Reference 33

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This paper cites Choreographer: Learning and Adapting Skills in Imagination.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Choreographer: Learning and Adapting Skills in Imagination

Reference 34

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Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Mismatched no more: Joint model-policy optimization for model- based rl,

Reference 35

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Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Differen- tiable mpc for end-to-end planning and control,

Reference 36

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Reference 37

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Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Measures of distance between probability distributions,

Reference 38

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This paper cites Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming

Reference 39

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Observation ce6fd07d-e6c5-4bb2-a43a-1b59251b0e2e · outbound

This paper cites When to trust your model: Model-based policy optimization,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes When to trust your model: Model-based policy optimization,

Reference 40

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This paper cites Model-based reinforcement learning via meta-policy optimization,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Model-based reinforcement learning via meta-policy optimization,

Reference 41

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This paper cites The virtues of laziness in model-based rl: A unified objective and algo- rithms,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes The virtues of laziness in model-based rl: A unified objective and algo- rithms,

Reference 42

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This paper cites Iterative value-aware model learning,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Iterative value-aware model learning,

Reference 43

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This paper cites Model-based value expansion for efficient model-free rein- forcement learning,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Model-based value expansion for efficient model-free rein- forcement learning,

Reference 44

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This paper cites Villani et al.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Villani et al

Reference 45

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This paper cites Generative adversarial nets,.

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Reference 46

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This paper cites Towards Principled Methods for Training Generative Adversarial Networks.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Towards Principled Methods for Training Generative Adversarial Networks

Reference 47

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Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Wasserstein generative ad- versarial networks,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:13:12.814759Z

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This paper cites Harpy, a connected speech recognition system,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Harpy, a connected speech recognition system,

Reference 49

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Observation 44c6830e-c21a-4e80-bd0a-d0cdc6c7c663 · outbound

This paper cites Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Reference 50

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This paper cites Walk Wisely on Graph: Knowledge Graph Reasoning with Dual Agents via Efficient Guidance-Exploration.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Walk Wisely on Graph: Knowledge Graph Reasoning with Dual Agents via Efficient Guidance-Exploration

Reference 51

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Observation 4ae52c77-d93e-43f9-b08d-39c637e62b6b · outbound

This paper cites Spectral Norm Regularization for Improving the Generalizability of Deep Learning.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Spectral Norm Regularization for Improving the Generalizability of Deep Learning

Reference 52

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Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Categorical Reparameterization with Gumbel-Softmax

Reference 53

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This paper cites Introduction to online convex optimization,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Introduction to online convex optimization,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:13:12.603409Z

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Observation 6d0d3d94-3f37-47e5-841f-80391b92d272 · outbound

This paper cites Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function

Reference 55

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This paper cites Visualizing data using t-sne.,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Visualizing data using t-sne.,

Reference 56

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Observation 10f6f2d4-73a8-4e7e-8c07-df67b7a7e86f · outbound

This paper cites General boundary conditions for denumberable markov processes,.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes General boundary conditions for denumberable markov processes,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:13:12.519612Z

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Observation 51b87c37-82ee-431a-aae4-056eb7bf6398 · outbound

This paper cites an unresolved cited work.

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:13:12.478583Z

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