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Kowshik chilamkurthy
Kowshik chilamkurthy

758 Followers

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Published in

DataDrivenInvestor

·Pinned

P-DQN: An Unique Algorithm for Discrete-Continuous Hybrid Action Space

Brief Introduction to RL Reinforcement Learning is a subfield of machine learning that teaches an agent how to choose an action from its action space. It interacts with an environment, in order to maximise rewards over time. Complex enough? let’s break this definition for better understanding. Agent: The program you train, with the aim…

Reinforcement Learning

5 min read

P-DQN: An Unique Algorithm for Discrete-Continuous Hybrid Action Space
P-DQN: An Unique Algorithm for Discrete-Continuous Hybrid Action Space
Reinforcement Learning

5 min read


Oct 24, 2022

Reinforcement Learning for Optimal Station Policy

Problem Statement Suppose you are in a SQUARE playground and a BALL pops up RANDOMLY (but uniformly) in the playground . Your job is to collect the ball and ‘’Wait For The Next Ball’’ to pop up. The next ball pops up after a fixed waiting time only after you collect the…

4 min read

Reinforcement Learning for Optimal Station Policy
Reinforcement Learning for Optimal Station Policy

4 min read


Published in

DataDrivenInvestor

·Sep 12, 2022

Hold Your Horses, My Dear Reinforcement Learning Agent

Stopping RL Agent From Taking Erratic Action Jumps — Introduction One of the biggest challenges for reinforcement learning experts is that they can’t control the agent’s action behavior. Sometimes making the agent converge and maximizing the rewards is not enough, you also want your agent to have smoothened actions. Let’s look at a few examples: Trading In trading, the biggest force…

Reinforcement Learning

4 min read

Hold Your Horses, My Dear Reinforcement Learning Agent
Hold Your Horses, My Dear Reinforcement Learning Agent
Reinforcement Learning

4 min read


Published in

Analytics Vidhya

·Aug 1, 2022

(1/2) Same Story(MLE) Different Endings: Mean Square Error, Cross Entropy, KL Divergence

Mathematically Proving That They are All the Same — Introduction Very often, data scientists and machine learning practitioners don’t appreciate the mathematical and intuitive relationships between different loss metrics like Negative Log Likelihood, Cross Entropy, Maximum Likelihood Estimation, Kullback-Leibler (KL) divergence, and most importantly Mean Square Error. Wouldn’t you be surprised if I say that KL-Divergence and Mean Square Error…

Machine Learning

5 min read

(1/2) Same Story(MLE) Different Endings: Mean Square Error, Cross Entropy, KL Divergence
(1/2) Same Story(MLE) Different Endings: Mean Square Error, Cross Entropy, KL Divergence
Machine Learning

5 min read


Published in

The Enlightened Indian

·Jan 30, 2022

How Caste System Born and Functions In India — Part — 1

Penning my understanding from the writings of Dr.B.R Ambedkar — Introduction Several studied the tremendous societal, economical and political consequences that “caste problem” inflict on India. It is sometimes seen as a tool for exclusion or as a tool for aggregation. Theoretically, it seems to bring people close overall: it helps improve the cohesiveness amongst groups while increasing the distance between…

4 min read

How Caste System Born and Functions In India — Part — 1
How Caste System Born and Functions In India — Part — 1

4 min read


Nov 4, 2021

RL vs Optimal Control: LQR for Trajectory Tracking (With Python Code)

Introduction In this blog series, we will learn about classical methods in optimal control which in someway laid a solid foundation for more familiar topics like reinforcement learning. There is an inevitable common boundary between these two fields and this series is aimed to propose these formal methods in optimal control…

Reinforcement Learning

6 min read

RL vs Optimal Control: LQR for Trajectory Tracking (With Python Code)
RL vs Optimal Control: LQR for Trajectory Tracking (With Python Code)
Reinforcement Learning

6 min read


Published in

Analytics Vidhya

·Oct 6, 2021

Imitate with Caution: Offline and Online Imitation

Behavioural Cloning, Data Aggregation Approach: DAGGER. — What’s Imitation Learning ? As the same itself suggests, almost every species including humans learn by imitating and also improvise. That’s evolution in one sentence. Similarly we can make machines mimic us and learn from a human expert. …

Imitation Learning

5 min read

Imitate with Caution: Offline and Online Imitation
Imitate with Caution: Offline and Online Imitation
Imitation Learning

5 min read


Published in

Nerd For Tech

·Jun 18, 2021

A Unique Intersection of Game Theory and Data Science: E-Commerce Product Pricing

Price Elasticity, Cross Elasticity and Nash Equilibrium — Contents: 1. Introduction 2. Concept of Elasticity 3. Measuring Elasticity: Linear Regression 4. Example: Data & Code 5. Dynamic Pricing in Competition: Game Theory 6. Nash Equilibrium Introduction One of the biggest challenges in e-commerce is to utilize data mining methods for the improvement of their dynamic pricing policies. Usually these products…

Game Theory

9 min read

A Unique Intersection of Game Theory and Data Science: E-Commerce Product Pricing
A Unique Intersection of Game Theory and Data Science: E-Commerce Product Pricing
Game Theory

9 min read


Published in

Nerd For Tech

·May 29, 2021

Quick Game Theory Blog Series For Dummies

6 -blog series Each less than 5 Minutes — Game Theory: The prelude Intention to write this series of blogs to introduce game theory to readers at an introductory level without requiring…medium.com Game Theory: Story of Thinking In this blog, we will discuss about thinking, which is inevitable process before any decision making. We will lay…kowshikchilamkurthy.medium.com Game Theory: Contention and Cross-Effects We have so far discussed decision problems that a rational individual could face. But as we move more closer to the…kowshikchilamkurthy.medium.com

Game Theory

1 min read

Quick Game Theory Blog Series For Dummies
Quick Game Theory Blog Series For Dummies
Game Theory

1 min read


Published in

Nerd For Tech

·May 29, 2021

Game Theory: Nash Equilibrium For Mixed Strategies ( Part 6 )

Continuous actions and Stochastic Strategic Games — Introduction We introduced Nash Equilibrium solution concept in the previous blog. In this blog we will start with a continuous action example and we will discuss the applicability of Nash equilibrium in mixed strategies. Mixed strategies are class of games where player chooses actions stochastically( i.e. …

Game Theory

6 min read

Game Theory: Nash Equilibrium For Mixed Strategies ( Part 6 )
Game Theory: Nash Equilibrium For Mixed Strategies ( Part 6 )
Game Theory

6 min read

Kowshik chilamkurthy

Kowshik chilamkurthy

758 Followers

RL | ML | ALGO TRADING | TRANSPORTATION | GAME THEORY

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