continuous-control

Discrete Codebook World Models for Continuous Control
In reinforcement learning (RL), world models serve as internal simulators, enabling agents to predict environment dynamics and future …
Aidan Scannell, Mohammadreza Nakhaei, Kalle Kujanpää, Yi Zhao, Kevin Luck, Arno Solin, Joni Pajarinen
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iQRL - Implicitly Quantized Representations for Sample-efficient Reinforcement Learning
Learning representations for reinforcement learning (RL) has shown much promise for continuous control. We propose an efficient …
Aidan Scannell, Kalle Kujanpää, Yi Zhao, Mohammadreza Nakhaei, Arno Solin, Joni Pajarinen
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iQRL - Implicitly Quantized Representations for Sample-efficient Reinforcement Learning
Quantized Representations Prevent Dimensional Collapse in Self-predictive RL
Learning representations for reinforcement learning (RL) has shown much promise for continuous control. We propose an efficient …
Aidan Scannell, Kalle Kujanpää, Yi Zhao, Mohammadreza Nakhaei, Arno Solin, Joni Pajarinen
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