Prisoner's Dilemma, Evolution of Cooperation Research Papers (original) (raw)

In 2012, the Liberal Democratic Party (LDP) released a draft of a new Japanese constitution. This is astonishing, because it intends to destroy all three principles of current constitution, or to renounce the modern constitutionalism. Despite the most important function of the constitution being the restriction of governmental power, the LDP/government is eager to abolish it, so the human rights of Japanese people are being threatened. We Japanese should rediscover the significance and roots of the current constitution.
It is generally believed that the current Constitution of Japan is simply based on a draft by GHQ/SCAP or General Douglas MacArthur. However, this recognition is not accurate. This paper, opposing such views, focuses on two stream of thinking, to which certain Japanese thinkers and politicians have been involved in: (1) One is Kempo Kenkyukai, including Iwasaburo Takano, Tatsuo Morito, and Yasuzo Suzuki, whose draft was conversely a basis of GHQ’s draft. In particular, Suzuki was one of the successors of the tradition of Japanese liberals led by Emori Ueki or Sakuzo Yoshino since the Meiji/Taisho era. (2) The other is the pacifism of Kijuro Shidehara, who originated the Article 9 which renounces war. They say it was just “imposed” by MacArthur, but this is not true, according to testimonies by Shidehara’s secretaries and friends. In reality, Shidehara himself asked MacArthur to “impose” it on Japanese government in order to save the Tenno system, and it is not just an ideal but a radical solution to the prisoner’s dilemma of armaments race.
These facts allow the recognition that the Japanese constitution is not simply “made in America,” because it was, at least partially, derived from the tradition of Japanese liberal thought. We should develop this tradition and re-achieve true modernization, so that the fundamental freedoms and human dignity of individuals are fully respected.

The goal of this thesis is twofold. First, intention recognition is studied from an Artificial Intelligence (AI) modeling perspective. We present a novel and efficient intention recognition method that possesses several important features: (i) The method is context-dependent and incremental, enabled by incrementally construct- ing a three-layer Bayesian Network model as more actions are observed, and in a context-dependent manner, relying on a logic programming knowledge base concern- ing the context; (ii) The Bayesian Network is composed from a knowledge base of readily specified and readily maintained Bayesian Network fragments with simple structures, enabling an efficient acquisition of the corresponding knowledge base (ei- ther from domain experts or else automatically from a plan corpus); and, (iii) The method addresses the issue of intention change and abandonment, and can appro- priately resolve the issue of multiple intentions recognition. Several aspects of the method are evaluated experimentally, achieving some definite success. Furthermore, on top of the intention recognition method, a novel framework for intention-based decision making is provided, illustrating several ways in which an ability to recognize intentions of others can enhance a decision making process.
A second subgoal of the thesis concerns that, whereas intention recognition has been extensively studied in small scale interactive settings, there is a major shortage of modeling research with respect to large scale social contexts, namely evolution- ary roles and aspects of intention recognition. Employing our intention recognition method and the tools of evolutionary game theory, this thesis explicitly addresses the roles played by intention recognition in the final outcome of cooperation in large populations of self-regarding individuals. By equipping individuals with the capacity for assessing intentions of others in the course of social dilemmas, we show how in- tention recognition is selected by natural selection, opening a window of opportunity for cooperation to thrive, even in hard cooperation prone games like the Prisoner’s Dilemma.
In addition, there are cases where it is difficult, if not impossible, to recognize the intentions of another agent. In such cases, the strategy of proposing commitment, or of intention manifestation, can help to impose or clarify the intentions of others. Again using the tools of evolutionary game theory, we show that a simple form of commitment can lead to the emergence of cooperation; furthermore, the combination of commitment with intention recognition leads to a strategy better than either one by itself.

From BYU Studies Quarterly: "Game theory has been applied to a number of disciplines, including economics, law, politics, sociology, and Bible studies, but this article is the first serious attempt to apply it to the Book of Mormon narrative. One particularly important model in game theory is known as the Prisoner's Dilemma, which emphasizes the possibility and benefits of cooperation in the face of conflict. The Book of Mormon account is an almost constant narrative based on conflict, first within the family of Lehi and then between two warring factions that arise from a split in that original Book of Mormon family. These conflicts tend to fit the Prisoner's Dilemma model extremely well. In a final estimation, the Prisoner's Dilemma and its application in the Book of Mormon provide another way of looking at the Book of Mormon's core messages of atonement, redemption, and the gospel of Jesus Christ."

- by Robert Francis Schwartz
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- Economics, Game Theory, Decision And Game Theory, Mormonism

This is a sub-chapter of my book "Explaining Altruism and its Limits". It critically examines Axelrod's reinterpretation in terms of the Reiterated Prisoner's Dilemma (RPD) of Ashworth's historical study on the Live-And-Let-Live-System in WWI that occurred on some stretches of the Western Front.
The main points are:
- The RPD-Model captures hardly any of the actual causes that were identified by Ashworth. In particular, the most important cause, elite-status of the deployed troops, fall out of its scope.
- even if the RPD is accepted as a highly stylized desription of the Live-And-Let-Live-System, the most important part of the explanatory work is not done by the model, but by all the examinations, assumptions and principals that are needed to justify the choice of the model and it's parameter values
- because the model is not very robust, its accordance with empirical data (if we can speak of such an accordance in case of a highly stylized model at all), might be only accidental.

Intention recognition is ubiquitous in most social interactions among humans and other primates. Despite this, the role of intention recognition in the emergence of cooperative actions remains elusive. Resorting to the tools of evolutionary game theory, herein we describe a computational model showing how intention recognition co-evolves with cooperation in populations of self-regarding individuals. By equipping some individuals with the capacity of assessing the intentions of others in the course of a prototypical dilemma of cooperation – the repeated Prisoner’s Dilemma –, we show how intention recognition is favored by natural selection, opening a window of opportunity for cooperation to thrive. We introduce a new strategy (IR) that is able to assign an intention to the actions of opponents, on the basis of an acquired corpus consisting of possible plans achieving that intention, as well as to then make decisions on the basis of such recognized intentions. The success of IR is grounded on the unshameful exploitation of unconditional cooperators whilst remaining robust against unconditional defectors. In addition, we show how intention recognizers do indeed prevail against the most famous successful strategies of iterated dilemmas of cooperation, even in the presence of errors and reduction of fitness associated with a small cognitive cost for performing intention recognition.

- by The Anh Han
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- Collective Behavior, Cognitive Science, Artificial Intelligence, Game Theory

When making a mistake, individuals can apologize to secure further cooperation, even if the apology is costly. Similarly, individuals arrange commitments to guarantee that an action such as a cooperative one is in the others' best interest, and thus will be carried out to avoid eventual penalties for commitment failure. Hence, both apology and commitment should go side by side in behavioral evolution. Here we provide a computational model showing that apologizing acts are rare in non-committed interactions, especially whenever cooperation is very costly, and that arranging prior commitments can considerably increase the frequency of such behavior. In addition, we show that in both cases, with or without commitments, apology works only if it is sincere, i.e. costly enough.
Most interestingly, our model predicts that individuals tend to use much costlier apology in committed relationships than otherwise, because it helps better identify free-riders such as fake committers: `commitments bring about sincerity'.
Furthermore, we show that this strategy of apology supported by commitments outperforms the famous existent strategies of the iterated Prisoner's Dilemma.

A partir d'une interrogation sur les relations entre liberté et déterminisme, cet écrit prétend résumer la démarche adoptée par Jean-Jacques Rousseau pour poser puis résoudre le problème dont son fameux contrat social donne la solution. La thèse soutenue est en effet que ce problème est celui de la liberté dont dispose l'individu face au déterminisme social, face aux lois qui émergent nécessairement des interactions humaines et qui précèdent et règlent tout acte individuel. En établissant la validité d'une telle affirmation, ces quelques lignes traitent du thème proposé en éclairant d'un jour nouveau la pensée politique de Rousseau en s'aidant notamment de quelques exemples empruntés à la théorie des jeux.

Hobbes postulates a social contract to formalize our collective transition from the state of nature to civil society. The prisoner’s dilemma challenges both the mechanics and the outcome of that thought experiment. The incentives for reneging are supposedly strong enough to keep rational persons from cooperating. This paper argues that the prisoner’s dilemma undermines a position Hobbes does not hold. The context and parameters of the social contract steer it safely between the horns of the dilemma. Specifically, in a setting as hostile as the state of nature, Hobbes’s emphasis on self-interest places a premium on survival, and thereby on adaptability, which then promotes progressive concessions toward peaceful coexistence. This transforms the relevant model of rationality from utility maximization to utility satisficing, thus favoring the pursuit of a mutually satisfactory outcome over that of the best personal outcome. The difference not only obviates the prisoner’s dilemma but also better approximates the state of nature while leaving a viable way out.

- by Necip Fikri Alican
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- Social Contract Theory, Thomas Hobbes, Hobbes, Thomas, State of Nature

The mechanisms of emergence and evolution of cooperation in populations of abstract individuals with diverse behavioural strategies in co-presence have been undergoing mathematical study via Evolutionary Game Theory, inspired in part on Evolutionary Psychology. Their systematic study resorts as well to implementation and simulation techniques, thus enabling the study of aforesaid mechanisms under a variety of conditions, parameters, and alternative virtual games. The theoretical and experimental results have continually been surprising, rewarding, and promising. Recently, in our own work we have initiated the introduction, in such groups of individuals, of cognitive abilities inspired on techniques and theories of Artificial Intelligence, namely those pertaining to both Intention Recognition and to Commitment (separately and jointly), encompassing errors in decision-making and communication noise. As a result, both the emergence and stability of coop- eration become reinforced comparatively to the absence of such cognitive abilities. This holds separately for Intention Recognition and for Commitment, and even more when they are engaged jointly. The present paper aims to sensitize the reader to these Evolutionary Game Theory based studies and issues, which are accruing in importance for the modelling of minds with machines, with impact on our understanding of the evolution of mutual tolerance and cooperation. In doing so, it also provides a coherent bird’s-eye view of our own varied recent work, whose more technical details and results are spread throughout a number of well recognized publishing venues, and to which we refer the reader for a fuller support of our claims where felt necessary.

It seems obvious that as the benefits of cooperation increase, the share of cooperators in the population should also increase. It is well known that positive assortment between cooperative types, for instance in spatially structured populations, provide better conditions for the evolution of cooperation than complete mixing. This study demonstrates that, assuming positive assortment, under most conditions higher cooperation benefits also increase the share of cooperators. On the other hand, under a specified range of payoff values, when at least two payoff parameters are modified, the reverse is true. The conditions for this paradox are determined for two-person social dilemmas: the Prisoner's Dilemma, the Hawks and Doves game, and the Stag Hunt game, assuming global selection and positive assortment.

The prisoner's dilemma was used to examine the cooperative and social effectiveness hypotheses of the General Factor of Personality (GFP). Consistent with both hypotheses participants who cooperated in the initial round scored higher on the GFP. However, this relationship was attenuated when controlling for life history strategy. Consistent with the social effectiveness hypothesis, a second round of the prisoner's dilemma revealed that participants higher in GFP were more likely to follow a tit-for-tat strategy and this finding remained when controlling for life history strategy. The results show the potential of using games to examine the nature of the GFP and predictions from life history theory. Future research could vary elements of the methods such as playing more iterations of the game and could also utilize different games.

Individuals make commitments towards others in order to influence others to behave in certain ways. Most commitments may depend on some incentive that is required to ensure that the action is in the agent's best interest and thus, should be carried out to avoid eventual penalties. Similarly, individuals may ground their decision on an accurate assessment of the intentions of others. Hence, both commitments and intention recognition go side by side in behavioral evolution. Here, we analyze the role played by the co-evolution of intention recognition plus the emergence of commitments, in the framework of the evolution of cooperative behavior. We resort to tools of evolutionary game theory in finite populations, showing how the combination of these two aspects of human behavior can enhance the emergent fraction of cooperative acts under a broad spectrum of configurations.

- by The Anh Han
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- Collective Behavior, Artificial Intelligence, Game Theory, Human Evolution

Agents make commitments towards others in order to influence others in a certain way, often by dismissing more profitable options. Most commitments depend on some incentive that is necessary to ensure that the action is in the agent's interest and thus, may be carried out to avoid eventual penalties. The capacity for using commitment strategies effectively is so important that natural selection may have shaped specialized capacities to make this possible. Evolutionary explanations for commitment, particularly its role in the evolution of cooperation, have been actively sought for and discussed in several fields, including Psychology and Philosophy. In this paper, using the tools of evolutionary game theory, we provide a new model showing that individuals tend to engage in commitments, which leads to the emergence of cooperation even without assuming repeated interactions. The model is characterized by two key parameters: the punishment cost of failing commitment imposed on either side of a commitment, and the cost of managing the commitment deal. Our analytical results and extensive computer simulations show that cooperation can emerge if the punishment cost is large enough compared to the management cost.

- by The Anh Han
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- Collective Behavior, Cognitive Psychology, Artificial Intelligence, Human Evolution

When starting a new collaborative endeavor, it pays to establish upfront how strongly your partner commits to the common goal and what compensation can be expected in case the collaboration is violated. Diverse examples in biological and social contexts have demonstrated the pervasiveness of making prior agreements on posterior compensations, suggesting that this behavior could have been shaped by natural selection. Here, we analyze the evolutionary relevance of such a commitment strategy and relate it to the costly punishment strategy, where no prior agreements are made. We show that when the cost of arranging a commitment deal lies within certain limits, substantial levels of cooperation can be achieved. Moreover, these levels are higher than that achieved by simple costly punishment, especially when one insists on sharing the arrangement cost. Not only do we show that good agreements make good friends, agreements based on shared costs result in even better outcomes.

"Few problems have created the combined interest of so many unrelated areas as the evolution of cooperation. As a result, several mechanisms have been identified to work as catalyzers of cooperative behavior. Yet, these studies, mostly grounded on evolutionary dynamics and game theory, have neglected the important role played by intention recognition in behavioral evolution. Here we address explicitly this issue, characterizing the dynamics emerging from a population of intention recognizers. We derive a Bayesian Network model for intention recognition in the context of repeated social dilemmas and evolutionary game theory, by assessing the internal dynamics of trust between intention recognizers and their opponents. Intention recognizers are then able to predict the next move of their opponents based on past direct interactions, which, in turn, enables them to prevail over the most famous strategies of repeated dilemmas of cooperation,
even in presence of noise. Overall, our framework offers new insights on the complexity and beauty of behavioral evolution driven by elementary forms of cognition."

Given its ubiquity, scale and complexity, few problems have created the combined interest of so many unrelated areas as the evolution of cooperation. Using the tools of evolutionary game theory, here we address, for the first time, the role played by intention recognition in the final outcome of cooperation in large populations of self-regarding individuals. By equipping individuals with the capacity of assessing intentions of others in the course of repeated Prisoner's Dilemma interactions, we show how intention recognition opens a window of opportunity for cooperation to thrive, as it precludes the invasion of pure cooperators by random drift while remaining robust against defective strategies. Intention recognizers are able to assign an intention to the action of their opponents based on an acquired corpus of possible intentions. We show how intention recognizers can prevail against most famous strategies of repeated dilemmas of cooperation, even in the presence of errors. Our approach invites the adoption of other classification and pattern recognition mechanisms common among Humans, to unveil the evolution of complex cognitive processes in the context of social dilemmas.

- by The Anh Han and +1
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- Collective Behavior, Cognitive Psychology, Cognitive Science, Artificial Intelligence