Tag: political-strategy

  • 5 Game Theory Models in Action: Historical Decisions That Follow Logic

    5 Game Theory Models in Action: Historical Decisions That Follow Logic

    Introduction

    Human Beings are social animals. Since the development of their cognition, humans have developed various kinds of tactics and strategies to survive and evolve at both personal and social levels. Game theory is the science related to strategy, developed in conjunction with mathematical models, to determine the best outcomes with respect to the implemented strategy.

    Although officially, game theory was developed by the Hungarian-American mathematician John von Neumann and the German-American economist Oskar Morgenstern in the 1940s, the various “Games” or strategies had been used by human civilizations throughout history. They had taken important decisions for their survival across different cultures and societies on earth, based on their Nash Equilibria. Now, a Nash Equilibrium is a situation inside a game, in which none of the players can improve their state through strategies, without changing the strategies of other players. Its name comes from its developer, the American mathematician John Nash. In the Nash Equilibrium, all players are basically in their best response state and will remain so until one or more players deviate to other strategies. Many games have been developed and studied among the economic, mathematical, business, and even philosophical circles. Each games create a certain interactive situation, with a certain Nash equilibrium, or equilibria. In this blog, we discuss the five most famous games and strategies, along with one historical example for each, showing how certain geopolitical powers acted and reacted in accordance with their specific Nash Equilibrium. So, let’s begin.

    Chapter 1: Prisoner’s Dilemma

    The Prisoner’s Dilemma is perhaps the most well-known, studied, and discussed game in game theory. It is a paradoxical situation developed, which includes two players, each deciding for their general self-interest without knowing the decision of the other. Let us imagine a situation: The police arrested two different individuals on suspicion of robbery in a building. They are kept in two separate cells such that they cannot interact with each other in any possible way. Now, the police went to the individual suspects and gave the following offer. If both of them confess to doing the robbery, both get 3 years of imprisonment. If neither confesses, they get 1 year of imprisonment. But, if one of them confesses to having robbed together while the other denies, the one who confessed is immediately released by the police, while the one who denied gets 10 years of imprisonment. Let us consider the two suspects, A and B. So, the following situation arises:-


    From the table, let us assess the choices of both A and B. As they cannot contact each other, their individual decisions should be based on assumptions about the other. So, if we consider that B confessed, the best decision A has is also to confess, as 3 years imprisonment is better than 10. Similarly, if B didn’t confess, the best decision for A is still confessing, as he would be released instead of serving 1 year of imprisonment. The situation is the same from B’s side. So, both confess and arrive at the Nash Equilibrium, which is confessing.

    Now, let us consider the Trench War Stalemate on the Western Front during the First World War in 1914. The German and Allied forces clashed in Belgium and France. But after both sides failed to achieve a decisive breakthrough, they dug continuous trenches in the ground to avoid catastrophic losses. After months of a potential stalemate, the options the armies had were to restrain, retreat, or continue bombardment. Although at first glance, restraint sounds like the best option in a stalemate, none of the armies could afford to do so without knowing the motives of the other. If one party had stopped bombarding and attacking, there could have been a possible “10-year prison” situation as mentioned before. Also, they could not run away, as this would lead to an unavoidable defeat. So, even after months and years, the two parties continued their aggression till 1918, in order to maintain the Nash Equilibrium of the Prisoner’s Dilemma game.

    Chapter 2: Game of Chicken

    The Game of Chicken is a very different model from the Prisoner’s Dilemma. In this game, there is not one but two Nash Equilibria. Let us consider a situation in which there are two drivers, A and B, driving their two cars towards each other. They had the pre-made agreement that the one who swerves will be trolled by being labelled as a chicken. Now, if none of them swerves and drives full speed toward each other, they will ultimately crash, resulting in severe injury, if not death. Let us consider the injury or death as 0 (the worst possible outcome), being called a chicken as 1 (the second worst outcome), the opponent as 3 (the highest positive outcome), and both swerve as 2 for each (as they neither won nor lost). So, the situation is as follows:-

    So, even though the safest outcome looks like both swerving, that may lead to humiliation for both. Also, neither of them swerving can lead to serious injury or death. Thus, unlike the Prisoner’s dilemma, the best possible outcome is if both players make the opposite decision from each other, i.e., only one of them swerves. This leads to two Nash Equilibria: either Driver A swerves or Driver B swerves and accepts the humiliation of being called a chicken.

    An example of this game is the Kargil War Resolution in 1999. At that time, both India and Pakistan were recent nuclear powers. In May 1999, Pakistani forces and militants illegally occupied high-altitude positions on the Indian Side of the Line of Control (LoC), which is a militarily sensitive region, in the hope of altering the status quo. Indian forces retaliated, and soon the 4th Indo-Pak war, also known as the Kargil war (Kargil being the region), began. India launched strategic, high-altitude operations while avoiding crossing the LoC. Pakistan, on the other hand, faced growing international pressure. Neither force could retreat at first, as it was a matter of pride and honor. For Indians, Kargil was legally part of their motherland, while for Pakistanis, it was their newly occupied territory. Thus, the war continued for two and a half months, until the Pakistani forces retreated. Already hammered and predicting more upcoming devastation, they had to accept defeat. The Indian forces, on the other hand, became victorious and restored the pre-conflict status quo. Thus, both parties attained the Nash Equilibrium of the Game of Chicken.

    Chapter 3: Stag Hunt

    Another interesting game, or model, is the Stag Hunt. It was devised by the French Philosopher, Jean Jacques Rousseau. As per the game, two hunters, A and B, could hunt together a stag, which is a large meal, or could hunt rabbits individually. But hunting together needs trust, as one could always betray the other. Also, hunting a stag alone is very difficult as it is a large beast. Here, we give credit to their accomplishments. If both successfully hunt the stag, we give 10 to each. If they individually hunt rabbits, each gets 2. If one goes for the stag and the other goes for the rabbit, the one hunting the stag is almost certain to fail and gets 0, while the one who goes for the rabbit gets 4, as he is the only successful hunter. Thus, the following matrix describes the situation:-

    From the matrix, we see that neither the hunter will go to hunt the stag alone, resulting in two possible Nash Equilibria: they either hunt the stag together or hunt rabbits individually. Although hunting a stag will give a better outcome, there exists a possibility of betrayal, whereas hunting rabbits gives a lesser outcome but no chance of betrayal, thus resulting in two different kinds of equilibria. The Stag Hunt model thus has two solutions: one based on more profit and the other based on more security.

    A real-life great geopolitical example for this model occurred more than two millennia ago, at the Battle of Salamis in 480 BCE. When Emperor Xerxes (Kshayarshsa in Old Persian) of the Achaemenid (Haxamanesi in Persian) Empire invaded Greece, many Greek states, of different customs and culture, allied under the Athenian general Themistocles. Thus, we see how the Greeks approached a trust-based Stag Hunt equilibrium, thus finally leading to their victory. If they hadn’t allied, it would have been nearly impossible to hunt a stag named Xerxes. 

    Chapter 4: Battle of the Sexes

    Let us suppose a couple where the man wants to watch an action movie together, while the woman wants to watch a romantic movie together. This situation gives rise to a game theory model called the Battle of the Sexes. In this situation, both want to watch the movie of their choice, but together. So, let us give ratings to their satisfaction levels. If both watch different movies, their satisfaction rating is zero, as they feel lonely, not surrounded by their loved ones. But if both watch the same movie, the person whose preferred movie is chosen is more satisfied, getting a satisfaction rating of 2, while the one who compensates for the movie to be with his or her partner gets a satisfaction rating of 1. This results in the following matrix:-

    In this game, we see that to achieve equilibrium, one of them must compensate and achieve a lower level of satisfaction. Thus, the Battle of the Sexes also has two equilibria where one achieves a lower level of satisfaction than the other.

    A classic example of this model is the imperial court arrangement of the Tokugawa Shogunate in Japan from the 17th to the 19th century. Japan, at that time, had two parallel sources of legitimacy: The Emperor in Kyoto, the sacred, ritualistic, and symbolic authority, and the Shogun in Edo (modern Tokyo), the military, administrative, and real power. In the 1600s, Tokugawa Ieyasu became the Shogun after centuries of chaos. He had 3 choices: if the Shogun dominated, a potential rebellion may arise due to moral illegitimacy; if the Emperor dominated, the chaos resumes,  and the only realistic choice was that both powers cooperate with some sort of compensation. Thus, the imperial court was designed such that the Emperor remained as the ceremonial head, while the Shogun took over the administrative, financial, and military powers. Thus, the Shoguns settled with more satisfaction, while the Emperors settled with a little less but were still satisfied. This system of equilibrium with respect to the Battle of the Sexes continued for more than 250 years till the Meiji restoration in the 1860s. 

    Chapter 5: Zero-Sum Games

    The previous games we explored above were all non-zero-sum games, i.e., when one player wins, the other player doesn’t need to lose. But in zero-sum games, when one player gains something, the other player loses the same amount, so that the total outcomes of the strategy remain zero. For example, in a coin toss, if one side picks heads and the other picks tails, only one side wins, and the other side loses. In zero-sum games, the Nash equilibrium is not about trust, fear, coordination, or compromise, like in the previously mentioned models. The only sensible thing each player can do is to assume that their opponent will try to harm them and thus choose a strategy that limits the damage, even in the worst case. In short, strategies here are individualistic.

    An example of a real-life zero-sum game is the Great Game in Central Asia. In the 19th century,  two expanding powers faced each other in Asia: the British Empire in India and the Russian Empire moving south through Central Asia. The central buffer states between them included Afghanistan, Persia, and the Central Asian Khanates. Both had the ambition of influencing these regions. Their options included a formal alliance, open war, and complete withdrawal, with each resulting in a moral or practical defeat. Thus, both empires chose a fourth option, an option of constant rivalry, with espionage, proxy influence, diplomatic pressure, and local interventions. Thus, both sides chose a zero-sum strategy, and when one got a small win, the other suffered a small loss. They interacted independently based on their individual interests and settled into balance, not through cooperation but through mutual limitation.

    Conclusion

    In this blog, we see how mathematical models dominated human interactions and decision-making, even before they were officially formalized. Game theory, however, is not limited to only human beings, but also affects plants, animals, and even algorithms and AIs. Every decision made by them can be modelled into a game of game theory. So, studying these games, which are numerous in number, can benefit those who want to understand human psychology, business interactions, and geopolitical decisions.

    That’s all for this blog. Hope you find this interesting. Please like, comment, share, and subscribe to my newsletters to be notified of future blogs and updates. Finally, thank you for reading this piece, and wish you all a Happy New Year, 2026.

  • The Origins of Game Theory: Evolution, Adaptation, and Strategy Through the Ages

    The Origins of Game Theory: Evolution, Adaptation, and Strategy Through the Ages

    Introduction

    Human beings are social animals; through the process of evolution, mankind developed short-term tactics and long-term strategies in order to cooperate and exist together in a society and, in turn, a civilization.

    Game Theory is a branch of applied mathematics that uses models of strategic interactions where subjects or players make decisions that are interdependent. It is used to study decision making of animals, humans, and even computers. It was first developed by John Von Neumann and Oskar Morgenstern in 1944.

    In this blog, we are going to discuss the basic concepts of Game Theory with some popular examples, and also understand how decision-making and strategy evolved from the genetic or individual level to society to the civilizational level.

    Chapter 1 – The Game Theory Primer: Models of conflict & cooperation

    The Prisoner’s Dilemma-

    Let us suppose two people, A and B, have been caught as suspects for a crime, but the police have no hard evidence. So they took the two prisoners separately and gave them a choice- either to confess or not, with the condition that- 

    i. If both confess, they get deserved punishment, but on early parole, let it be 2 years.

    ii. If one confesses and the other denies, the one confessing is set free, let it be 0 years, and the other gets a harsher punishment, let it be 3 years.

    iii. If both deny, both are given even lighter punishment, as the police have no hard proof to give the actual punishment, let it be 1 year.

    So the condition that arises can be described in tabular form as this.

    B stays silentB confesses
    A stays silent1,13,0
    A confesses0,32,2

    Now, A does not know what B will choose. Suppose B stays silent, A will suffer less if he confesses, as 0 years are better than 1 year. Now, if B confesses, A will suffer less if he confesses because 2 years are better than 3 years.

    The same is also true from B’s point of view.

    Thus, both of them confess to making the best decision.

    This is the non-iterative form of the prisoner’s dilemma, that is, they don’t have to repeat the same thing again.

    Now, if the Prisoner’s Dilemma is repeated-

    To see this, Robert Axelrod, a political scientist, organized a computer game tournament in 1980. He invited many game theorists to participate in the tournament with their own unique programs, which were called strategies. In the tournament, each strategy was paired with another for a 200-round Prisoner’s Dilemma game. The whole tournament was repeated 5 times to make it precise. A total of 15 strategies participated, and the winner was a strategy called “ tit for tat”. It was designed such that it cooperated at first but defected once after its opponent defected, that is, it held a grudge only for the next round and then forgave. 

    All the top top strategies shared some qualities-

    1. They were nice and didn’t defect at first.
    2. They were forgiving and didn’t hold a grudge after 1 round.

    Then Alexrod organized a second tournament, with the only change being that no one knew the actual number of rounds. That time, a total of 63 strategies participated. The winner was again “tit for tat”.

    Apart from the first two qualities, Axelrod found two more qualities in top strategies-

    1. They retaliated immediately in the next round after being cheated.
    2. They were clear and simple.

    Although when tit for tat was later run against all nasty and defecting strategies, it came last, which shows there is no single best strategy; everything depends on the situation and surroundings. Although it was also seen that when there was some cooperation from other strategies, tit for tat and other good strategies, although being a minority, became dominant strategies soon. Later, it was found that tit for tat would do better if it retaliated 90% of the time instead of 100%. 

    Zero-Sum vs Non-Zero-Sum Games

    Zero-Sum games are those where one person’s win is another person’s loss. For example, tennis, chess, and most sports.

    Non-Zero-Sum games or strategies where one person’s outcome is independent of the other’s and vice versa. For Example- If there are two shops and only one customer, if he goes to one shop doesn’t mean a loss to the other shop, as he can go there too at a later time; in fact, he has neither gained nor lost anything.

    I would like to refer to Veritasium’s YouTube video titled “What Game Theory Reveals About Conflict and War” if anyone wants more details.

    Chapter 2- Evolution of Strategies at the Genetic and Individual Level

    The concept of Evolution in its true form was first described by Charles Darwin around 1859. Although before him many have inkings to the truth, it was Darwin who gave a structured theory to it. It is the evolution of strategies at the genetic level that helped us survive for millions of years. Each species has developed unique strategies to survive with its own set of morals. Black-headed gulls eat each other’s babies, and female Praying Mantises eat their male partners during mating for nutrition. Bees defend their nests/hives by stinging and, in turn, sacrificing their lives. Each organism has its own strategy, mostly to survive and pass on its genes.

    The more they replicate, the more the species survives. DNA acts as our replicator for survival. The British evolutionary biologist Richard Dawkins, in his book “The Selfish Gene,” suggests that it is more natural to be selfish than to be altruistic in order to survive.

    Now, let us consider a Hawk and a Dove interaction and assign points to the results-

    50 points for a win, 0 for a loss, -100 for being seriously injured, and -10 for wasting time over a long contest. These points can be thought of as being directly convertible into the currency of gene survival.

    In a single Hawk vs Dove interaction, Hawk will always win. If there are only Doves, the winner will get 50 points for winning and -10 for wasting time, so in total, he scores 40. The loser gets -10 for wasting time, so the total average payoff from this interaction is  (40-10)/2 =15. But now, if a mutant Hawk arrives in the population, he beats every dove and scores 50 each time; he enjoys a huge advantage over the doves, who usually get 15 on average. Hawk’s gene will thus rapidly spread through the population. But slowly the Hawks’ chances to win every fight will decrease, and at last, if there are only Hawks left, the winner will get 50, but the loser will get -100 for being seriously injured, resulting in the average result of interaction (50-100)/2= -25. But now a single Dove moves in the population, he will lose, but he manages to never get hurt, his average payoff is 0, while Hawks are usually getting -25, so Dove’s gene will survive and spread through the population. The stable ratio of Hawks and Doves turns out to be (7/12) and (5/12). At this point, the average pay off of both the Hawks and the Doves is equal to about 6(¼).

    This model also applies to human beings. Apart from the Hawk and the Dove strategies, there are other strategies like the Retaliator, which plays like a Dove in the beginning but retaliates when attacked by a Hawk. There is also the Bully who behaves like a Hawk until someone hits back, then he runs away. Another strategy is the Prober-Retaliator, who behaves like a Retaliator but occasionally tries experimental escalation of the contest. He behaves like a Hawk if his opponent does not fight back, and if opponents fight back, he reverts to conventional threatening like a Dove.

    Among the five strategies in a computer simulation, the Retaliator emerges as the most stable, followed by Prober-Retaliator, which is nearly stable. Although this result, the implementation of strategies varies from one situation to another.

    Each individual has a much closer relationship with individuals with whom they share more genetic information or relatedness. An individual is closer to his parents because he shares 50% genes with both his father and mother, and their relatedness is thus (½). The relatedness between two brothers is also (½) as they share 50% of genes. The formula for relatedness can be written as m*(½)^n, where m is the number of common ancestors, and n is the generational distance. For example, the first cousins have two common ancestors and their generational distance is 4, so the relatedness will be 2*(½)^4=(⅛). Thus, a man is closer to his sibling than his first cousin.

    So in this chapter, we see that individuals form groups and associations or act solo based on the strategies of their survival. This chapter also reveals that game theory doesn’t just apply to economics or war- it’s deeply rooted in biology & life.

    Chapter 3- Homo sapiens & the Rise of Civilizations

    Homo sapiens, or the modern human, arrived on Earth about 300,000 years ago in Africa, and about 150,000 years ago, they began to spread to the rest of the world. Before that, there were many other species of humans living in Afro-Eurasia, such as Homo neanderthalensis and Homo erectus. But around 70,000 years ago, something occurred which made Homo sapiens superior to other human species and slowly drove them extinct- The Cognitive Revolution. Due to this, Homo sapiens developed the art of gossiping and telling stories, which enabled them to form larger groups compared to their counterparts. Imagination and gossip created ideas that continued to live even after the creators were dead. This enabled two individuals with no records of previous encounters to begin working together under a common idea. According to historian Yuval Noah Harari and his book “Sapiens: A Brief History of Humankind”, the Cognitive Revolution is accordingly the point when history declared its independence from biology.

    The Cognitive Revolution also enabled Homo sapiens to travel from one place to another in a group in an efficient way; they were the only species of humans to arrive in the New World. The stories they created soon got embedded in their culture, giving rise to myths and religions around which the earliest settlements were made.

    Then, around 12,000 years ago, came another important point of human history- the Agricultural Revolution. As a result, human beings weren’t required to live their life as hunter-gatherers and thus began to settle down around rivers or areas suitable for agriculture. This resulted in history’s first towns and cities being formed in areas like the Fertile Crescent, the Nile River Valley, the Indus River Valley, the Yellow River Valley, and around the eastern coasts of the Mediterranean Sea. That was also the time when the domestication of animals like sheep, goats, pigs, and chickens took place.

    Early society ran on barter systems of give and take. But it had a problem: to make a trade, each side was required to want what the other had to offer. Thus, money was created as a medium to systematically represent the value of other things for the purpose of exchanging goods & services. The earliest form of money was about 4000 years ago, when shells were used as money. Money soon developed in different regions of the world in different ways, which completely created a new direction for the evolution of mankind.

    Another important point in human evolution was the Scientific Revolution and the Age of Discovery around 1500 CE. Before that, the border between philosophy & science was not very clear, and scientific thoughts were mostly dominated by religions & theologies all over the world. Due to the contribution of geniuses like Nicolaus Copernicus, Galileo Galilei, Johannes Kepler & Sir Isaac Newton, a clear process of scientific thinking was invented, which was clearly distinct from philosophical & theological thoughts. This accelerated the progress of scientific studies, which in turn accelerated human evolution. Also, it was the 1500s when explorers & merchants like Christopher Columbus & Vasco da Gama began their journey of exploration and discovered new continents like America & new trade routes like throughthe Cape of Good Hope to India. Both the scientific revolution and the age of discoveries enabled a small continent like Europe to colonize most of the world, which further led to the world we see today.

    This chapter thus shows how human beings used storytelling, agriculture, and science to become the ultimate players in the game theory of life.

    Chapter 4- The Effect of Nature & Environment on Human Civilizational Strategies

    Globe

    The human societies that developed all around the world were directly affected by the following environmental variables: climate, geological type, availability of resources, area of landmass, terrain, and connectivity. We see that the early civilizations evolved faster around tropical or sub-tropical regions. For example, the Mesopotamian, Egyptian & Indus Valley Civilizations progressed at a faster rate compared to cultures in the Steppes. This was because the former regions get more direct sunlight compared to the latter regions. Since the early economy was agrarian, the places with more sunlight have more developed agriculture & economy. Also, rivers like the Euphrates, Tigris, Nile & Indus played an important role in providing water for irrigation, which the areas like the Arabian Peninsula didn’t receive much. The shape of the landmass also heavily affected the spread of culture and, in turn, growth. Historian Jared Diamond in “Guns, Germs & Steel” states that the cultures in Eurasia evolved faster than the cultures in the Mesoamerica and Sub-Saharan Africa because Asia and Europe are longer in the East-West direction thus the climate being same it was easier to communicate, where as America & Sub-Saharan Africa are longer in the North-South direction which hindered communication because of variation in latitudes and in charge climate.

    Also, some countries developed natural protections that protected them from foreign invasion to some extent. For Example, the Himalayas for India, the Tibetan Plateau & the Mongolian Plateau for China & the Sahara Desert for Egypt. This caused those countries to feel secure from early invasions and concentrate on their individual progress. The livestock also played an important role in the cultures, for example, the camel in the case of Egypt & the cow in the case of India.

    The ease of communication also got affected by the availability of nearby routes, which are tried & tested, thus the cities on the Silk Route slowly evolved into influential economic hubs.

    Later, after scientific & industrial evolutions in the 15th-16th & 18th-19th centuries, different criteria became more important. Colder countries began to develop more as there were easier to store rations, compared to hotter countries. Moreover, the disadvantages due to terrain & isolation disappeared because of the invention of railways, airways, telephones, mobile phones & internet.

    In the modern world, the civilizational game theory is less dependent on natural causes & more dependent on scientific, economic, military & political causes.

    Conclusion

    Thus, we conclude that game theory acts at different levels- genetic, individual, societal, geographic, civilizational, as well as economic & political. In understanding these games, it just won’t help us to understand history but also help us in discovering the hidden causes of genetic, human & civilizational progress.

    Let me know how you consider this blog, please like, comment & share if you find this interesting.

    Suggested Reading

    1. The Selfish Gene by Richard Dawkins
    2. Sapiens: A Brief History of Humankind by Yuval Noah Harari
    3. Guns, Germs & Steel by Jared Diamond

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