Shivang Shrivastav – Medium

Shivang Shrivastav

TD3 Code Implementation: Taming Continuous Control with Twin Delayed DDPG

From theory to practice: Translating TD3 into code for robust and stable continuous control

1d ago

TD3 Code Implementation: Taming Continuous Control with Twin Delayed DDPG

1d ago

Unveiling the Nuances: Dissecting the Differences Between DDPG and TD3

Understanding how TD3 addresses inefficiencies of DDPG and improves performance in continuous control tasks

1d ago

Unveiling the Nuances: Dissecting the Differences Between DDPG and TD3

1d ago

DDPG Code Implementation: Applying Actor-Critic Methods for Continuous Control

Training Ant to Run: Implementing DDPG for Mastering Locomotion in a Simulated Environment

2d ago

DDPG Code Implementation: Applying Actor-Critic Methods for Continuous Control

2d ago

DQN Code Implementation: Lunar Lander Descent with DQN and Pytorch Lightning

Lunar Lander: An AI Playground for Deep Reinforcement Learning

5d ago

DQN Code Implementation: Lunar Lander Descent with DQN and Pytorch Lightning

5d ago

A2C Code Implementation: Your Code Companion for Deep RL

Acrobat Robot trained by Advantage Actor Critic in Reinforcement Learning

5d ago

A2C Code Implementation: Your Code Companion for Deep RL

5d ago

REINFORCE Code Implementation: Mastering Policy Gradients for Reinforcement Learning

Balancing the Cart-Pole: A Practical Implementation of the REINFORCE Algorithm

5d ago

REINFORCE Code Implementation: Mastering Policy Gradients for Reinforcement Learning

5d ago

Generalized Advantage Estimation (GAE): A Deep Dive into Bias, Variance, and Policy Gradients

GAE: Balancing Bias and Variance for Efficient Policy Gradients

5d ago

Generalized Advantage Estimation (GAE): A Deep Dive into Bias, Variance, and Policy Gradients

5d ago

Proximal Policy Optimization (PPO): Clipping, Stability, and Sample Efficiency in Reinforcement…

Beyond Vanilla Policy Gradients: PPO for Enhanced Performance in Complex Environments

5d ago

Proximal Policy Optimization (PPO): Clipping, Stability, and Sample Efficiency in Reinforcement…

5d ago

DDPG: DQN Re-engineered for Continuous Action Spaces

How DDPG algorithm is built by modifying DQN in Reinforcement Learning

6d ago

DDPG: DQN Re-engineered for Continuous Action Spaces

6d ago

SAC vs. A2C: A Comparative Analysis of Reinforcement Learning Algorithms

Soft Actor-Critic (SAC): Unveiling the Power of Stochastic Policies for Optimal Control

Jan 5

SAC vs. A2C: A Comparative Analysis of Reinforcement Learning Algorithms

Jan 5

Shivang Shrivastav

Shivang Shrivastav

I am an A.I enthusiast. Passionate about learning Deep Learning and it’s applications. “Inquisitive by mind and Explorer by soul”, This is my approach.

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