Nash Equilibrium – A fundamental concept in game theory, depicts a scenario wherein each player’s chosen strategy is the best possible considering the choices made by other participants. In simpler terms, no player has any motivation to change their strategy alone, as this alteration would not result in a more favorable outcome for them. In this post, I will introduce an example of a chess game between me and my son, who is super smart. I will keep using this example, i.e., a game of chess between me and my son, in almost every blog post of relevance.

Nash Equilibrium – Introduction

“Nash” is the last name of a really smart person named John Nash. He was good at figuring out how people make choices in games and situations where they have to think about what others might do. Nash discovered a special idea called “Nash equilibrium.” It’s like when everyone makes their best choices, and even if they change their minds, they won’t do any better.

It serves as a tool to scrutinize decision-making and interactions, shedding light on the conduct and consequences of competitive entities in strategic contexts.

  • Chosen strategies are optimal based on others’ strategies, discouraging unilateral changes for better outcomes.
  • Represents a balanced state where adjustments by one company rely on coordinated changes by others for improved positions.
  • Frequently seen in competitive industries like market share, pricing, advertising, and resource allocation.
  • Provides valuable insights into strategic business interactions, decision-making, and responses to market shifts.
  • Influences the competitive landscape and outcomes within the industry by highlighting the dynamics of strategic interactions.

In the context of business, Nash equilibrium refers to a scenario in which competing firms or participants have reached a stable state in their decision-making strategies.

Nash Equilibrium In Game of Chess

Nash equilibrium indeed occur in a chess game, particularly in situations where players carefully consider their moves and responses based on their opponent’s decisions.

In chess, each player aims to maximize their chances of winning while simultaneously predicting their opponent’s potential moves. If both players reach a point where neither can gain an advantage by changing their strategy, a Nash equilibrium is achieved. This means that each player’s current move choice is optimal given the opponent’s moves, and any unilateral deviation from their chosen strategy would not lead to a better outcome for that player.

Nash equilibrium in chess highlights the strategic depth and complexity of the game, where players strive to find the best moves that balance the offense, defense, and overall game dynamics.

Example – Chess Game (Between Me and My Son)

Nash equilibrium signifies a stable balance where all players have discovered a point of equilibrium among their actions, and altering one’s strategy while others remain unchanged would not enhance a player’s position. It holds significant relevance across diverse domains, including economics, politics, evolutionary biology, and even today’s competitive business landscape.

Imagine me and my son are playing a game, like rock-paper-scissors. we both want to win, so we try to guess what the other person will do. Nash equilibrium is when we both make our best guesses, and even if we change our guess, we won’t do any better. It’s like finding a special spot in the game where I and my son are doing our best, and neither of us wants to change because it won’t help any of us win more. It’s a way to figure out the best choices to make in a game so that nobody wants to change their mind.

As we navigate the complexities of these realms, the concept of Nash equilibrium continues to shed light on the art and science of decision-making, ultimately shaping outcomes and influencing the way we approach challenges and opportunities.

The Game

  • When me and my son play chess, we both want to win and think carefully about each move.
  • Special point in the game where we both make our best moves based on what we think the other will do.
  • I will try to guess where my son will move his pieces, and he’ll try to guess my moves too.
  • At Nash equilibrium, my moves and my son’s moves are the best choices for both of us and changing them won’t help either win more.
  • It’s like finding a secret spot in the game where we both do our best, and neither of us wants to change because we already making the smartest moves we can.

It’s a way to find a balance where nobody wants to change because they’re already doing their best. Just like when you and your friends try to pick the best game to play, Nash’s idea helps people understand how to make the smartest choices when they’re playing games or making decisions together.

C++ Code

Below is a simple example of a chess game in C++ between me and my son. Please note that this is a simplified version for free subscribers and it does not implement all the rules of chess.

#include <iostream> 
#include <cstdlib>
// Function to display the chess board
void displayBoard(char board[8][8]) {
for (int i = 0; i < 8; ++i) {
for (int j = 0; j < 8; ++j) {
std::cout << board[i][j] << " ";
std::cout << std::endl;
} int main() {
char board[8][8] = {
{'r', 'n', 'b', 'q', 'k', 'b', 'n', 'r'},
{'p', 'p', 'p', 'p', 'p', 'p', 'p', 'p'},
{' ', ' ', ' ', ' ', ' ', ' ', ' ', ' '},
{' ', ' ', ' ', ' ', ' ', ' ', ' ', ' '},
{' ', ' ', ' ', ' ', ' ', ' ', ' ', ' '},
{' ', ' ', ' ', ' ', ' ', ' ', ' ', ' '},
{'P', 'P', 'P', 'P', 'P', 'P', 'P', 'P'},
{'R', 'N', 'B', 'Q', 'K', 'B', 'N', 'R'}
// Display the initial chess board

// Simulate moves between you and your "son"
// Your move
board[6][4] = ' ';
board[4][4] = 'P';

// Your "son's" move
board[1][3] = ' ';
board[3][3] = 'p';

// Continue simulating moves...

return 0; 

In this example, me and my “son” (the computer AI) take turns making moves by updating the board array to represent the chess pieces’ positions. Please note that this is a basic, for free subscribers of my blog and simplified implementation for illustrative purposes. A complete and fully functional chess game would require more intricate logic to handle legal moves, captures, check/checkmate conditions, and other chess rules, thus that can be covered only in paid version.

Food for Thought

In simple terms, Nash Equilibrium theory suggests that when people make choices in a game or situation, they try to predict what others will do. Just like in a chess game, each player thinks about the best move their opponent might make.

Nash Equilibrium is like a point where everyone’s choices are as good as they can be, and no one wants to change their decision. It’s like finding a special balance in the game.

In the real world of business, there can be a critical threshold where a slight change in strategy can lead to a major shift in outcomes. This is particularly relevant for organizations, as they often operate in competitive environments where small changes can have ripple effects. Identifying and understanding this tipping point can indeed influence how organizations approach their decision-making processes, helping them anticipate potential shifts and make more informed choices to stay ahead in dynamic situations.”

Similarly, just like scientists study and improve string theory to understand the universe better, people like me i.e. self-learners study Nash Equilibrium to understand how we make choices when we’re playing games or making decisions together.

Point to Note: 

All of my inspiration and sources come directly from the original works, and I make sure to give them complete credit. I am far from being knowledgeable in physics, and I am not even remotely close to being an expert or specialist in the field. I am a learner in the realm of theoretical physics.

Books + Other readings Referred

  • Open Internet, research papers & Conferences.
  • Hands on personal research work @AILabPage

Feedback & Further Question

Do you need more details or have any questions on topics such as technology (including conventional architecture, machine learning, and deep learning), advanced data analysis (such as data science or big data), blockchain, theoretical physics, or photography? Please feel free to ask your question either by leaving a comment or by sending us an  via email. I will do my utmost to offer a response that meets your needs and expectations.


Conclusion – Nash equilibrium is a powerful concept that transcends various domains, including gaming, business, and decision-making. It reveals the delicate balance that can emerge when participants optimize their strategies in response to others’ choices. Whether in chess, business competition, or other contexts, Nash equilibrium underscores the intricate interplay of actions and reactions. It serves as a lens through which we can understand and analyze complex scenarios, offering valuable insights into human behavior, strategic interactions, and the dynamics of competitive environments.

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Posted by V Sharma

A Technology Specialist boasting 22+ years of exposure to Fintech, Insuretech, and Investtech with proficiency in Data Science, Advanced Analytics, AI (Machine Learning, Neural Networks, Deep Learning), and Blockchain (Trust Assessment, Tokenization, Digital Assets). Demonstrated effectiveness in Mobile Financial Services (Cross Border Remittances, Mobile Money, Mobile Banking, Payments), IT Service Management, Software Engineering, and Mobile Telecom (Mobile Data, Billing, Prepaid Charging Services). Proven success in launching start-ups and new business units - domestically and internationally - with hands-on exposure to engineering and business strategy. "A fervent Physics enthusiast with a self-proclaimed avocation for photography" in my spare time.

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