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ML-Reinforcement

21 posts

Exploitation and Exploration in Machine Learning

Last Updated: 18 May 2024

Exploration and Exploitation are methods for building effective learning algorithms that can adapt and perform optimally in different environments. This article focuses on...read more

Machine Learning

ML-Reinforcement

Data Science Blogathon 2024

Agent-Environment Interface in AI

Last Updated: 21 April 2025

The agent-environment interface is a fundamental concept of reinforcement learning. It encapsulates the continuous interaction between an autonomous agent and its surround...read more

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ML-Reinforcement

Artificial Intelligence

Data Science Blogathon 2024

Reinforcement Learning in Python: Implementing SARSA Agent in Taxi Environment

Last Updated: 29 May 2024

SARSA (State-Action-Reward-State-Action) is an on-policy reinforcement learning algorithm that updates its policy based on the current state-action pair, the reward receiv...read more

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Machine Learning

ML-Reinforcement

Data Science Blogathon 2024

Multi-Agent Reinforcement Learning in AI

Last Updated: 29 May 2024

Reinforcement learning (RL) can solve complex problems through trial and error, learning from the environment to make optimal decisions. While single-agent reinforcement l...read more

Machine Learning

ML-Reinforcement

Data Science Blogathon 2024

Optimizing Production Scheduling with Reinforcement Learning

Last Updated: 06 June 2024

Production scheduling is a critical aspect of manufacturing operations, involving the allocation of resources to tasks over time to optimize various performance metrics su...read more

Machine Learning

ML-Reinforcement

Multi-armed Bandit Problem in Reinforcement Learning

Last Updated: 18 June 2024

The Multi-Armed Bandit (MAB) problem is a classic problem in probability theory and decision-making that captures the essence of balancing exploration and exploitation. Th...read more

Machine Learning

ML-Reinforcement

AI-ML-DS With Python

Data Science Blogathon 2024

Dyna Algorithm in Reinforcement Learning

Last Updated: 05 July 2024

The Dyna algorithm introduces a hybrid approach that leverages both real-world and simulated experiences, enhancing the agent's learning efficiency. This article delves in...read more

Machine Learning

ML-Reinforcement

Data Science Blogathon 2024

How to Visualize and Interact with Environments in Reinforcement Learning?

Last Updated: 23 September 2024

Reinforcement learning (RL) is a crucial area of machine learning where agents learn to make decisions by interacting with an environment. Visualization of these interacti...read more

Machine Learning

ML-Reinforcement

AI-ML-DS With Python

How to Make a Reward Function in Reinforcement Learning?

Last Updated: 01 October 2024

One of the most critical components in RL is the reward function. It drives the agent's learning process by providing feedback on the actions it takes, guiding it toward a...read more

Machine Learning

ML-Reinforcement

AI-ML-DS With Python

Model-Based Reinforcement Learning (MBRL) in AI

Last Updated: 03 June 2025

Model-based reinforcement learning is a subclass of reinforcement learning where the agent constructs an internal model of the environment's dynamics and uses it to simula...read more

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ML-Reinforcement

Artificial Intelligence

AI-ML-DS With Python

How Are Neural Networks Used in Deep Q-Learning?

Last Updated: 09 October 2024

Deep Q-Learning is a subset of reinforcement learning, a branch of artificial intelligence (AI) that focuses on how agents take actions in an environment to maximize cumul...read more

ML-Reinforcement

Machine Learning

AI-ML-DS With Python

Dynamic Programming in Reinforcement Learning

Last Updated: 28 May 2025

Dynamic Programming (DP) is a technique used to solve problems by breaking them down into smaller subproblems, solving each one and combining their results. In Reinforceme...read more

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Machine Learning

ML-Reinforcement

AI-ML-DS With Python

Policy Gradient Methods in Reinforcement Learning

Last Updated: 05 June 2025

Policy Gradient methods in Reinforcement Learning (RL) to directly optimize the policy, unlike value-based methods that estimate the value of states. These methods are par...read more

Machine Learning

ML-Reinforcement

What is policy in reinforcement learning?

Last Updated: 23 June 2025

Reinforcement learning is a type of machine learning where a agent like a robot or a program learns to make decisions by interacting with an environment. The agent takes a...read more

Machine Learning

ML-Reinforcement

Temporal Difference (TD) learning

Last Updated: 21 June 2025

Temporal Difference (TD) Learning is amodel-free reinforcement learning methodused by algorithms like Q-learning to iteratively learn state value functions (V(s)) or state...read more

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ML-Reinforcement

AI-ML-DS With Python