Temporal difference learning

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Reinforcement learning

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Related lectures (29)

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First steps toward deep reinforcement learning

Explores the shift to deep reinforcement learning through neural networks for direct policy learning, bypassing Q-values and V-values.

Quiz: policy gradient methods

Presents a quiz discussing claims related to reinforcement learning algorithms.

Deep Learning Agents: Reinforcement Learning

Explores Deep Learning Agents in Reinforcement Learning, emphasizing neural network approximations and challenges in training multiagent systems.

Model-Free Prediction in Reinforcement Learning: Key Methods

Covers model-free prediction methods in reinforcement learning, focusing on Monte Carlo and Temporal Differences for estimating value functions without transition dynamics knowledge.

Eligibility Traces for Policy Gradient and Actor-Critic

Explores eligibility traces in policy gradient and actor-critic architectures, leading to an elegant online learning rule.

Variations of SARSA: Expected SARSA and Q Learning

Explores expected SARSA and Q learning, two variations of the SARSA algorithm.

Feedback & Adaptation

Explores feedback and adaptation in visual intelligence, enhancing machine performance in dynamic environments.

Collective Learning Dynamics: Similarity Exploitation

Delves into collective learning dynamics with similarity exploitation, covering structured learning, adaptive frameworks, modeling, simulation, and experimental results.

Monte-Carlo Methods for Reinforcement Learning

Explores Monte-Carlo methods for reinforcement learning, comparing them with TD-methods and emphasizing the efficiency of TD methods in propagating information.