Strategic interaction in the Prisoner's Dilemma: A game-theoretic dimension of conflict research

This four-part enquiry treats selected theoretical and empirical developments in the Prisoner's Dilemma. The enquiry is oriented within the sphere of game-theoretic conflict research, and addresses methodological and philosophical problems embedded in the model under consideration. In Part One, relevant taxonomic criteria of the von Neumann- Morgenstern theory of games are reviewed, and controversies associated with both the utility function and game-theoretic rationality are introduced. In Part Two, salient contributions by Rapoport and others to the Prisoner's Dilemma are enlisted to illustrate the model's conceptual richness and problematic wealth. Conflicting principles of choice, divergent concepts of rational choice, and attempted resolutions of the dilemma are evaluated in the static mode. In Part Three, empirical interaction among strategies is examined in the iterated mode. A computer-simulated tournament of competing families of strategies is conducted, as both a complement to and continuation of Axelrod's previous tournaments. Combinatoric sub-tournaments are exhaustively analyzed, and an eliminatory ecological scenario is generated. In Part Four, the performance of the maximization family of strategies is subjected to deeper analysis, which reveals critical strengths and weaknesses latent in its decision-making process. On the whole, an inter-modal continuity obtains, which suggests that the maximization of expected utility, weighted toward probabilistic co-operation, is a relatively effective strategic embodiment of Rapoport's ethic of collective rationality

Environmental dilemmas revisited: structural consequences from the angle of institutional ergonomics

The structure of a social dilemma lies behind many environmental problems. Mingling temporal aspects of resources with the structure of the social dilemma often leads to wrong conclusions. Therefore, it is worth analytically separating temporal aspects from structural aspects of the dilemma. This article concentrates solely on the structural aspects of the dilemma and the grades of complexity with respect to the number and stakes of the people involved, as well as the asymmetry of endowments and the salience of the optimal use of the resource in order to come close to the welfare optimum. Dilemmas with sufficient complexity are extremely vulnerable to individual defectors, and therefore institutions are necessary for the solution of the dilemma. Consequently, research in environmental psychology should not only target the individuals, but focus on institutional design with respect to (1) the structural diagnosis of environmental dilemmas; (2) methods that provide an insight into the structural problem of environmental dilemmas; (3) the impact of institutions on internalizing norms; and (4) the impact of structural knowledge about the dilemma of accepting institutions that help to solve the environmental dilemma. In analogy to software-ergonomics, psychology should initiate research in institutional ergonomics that helps to create addressee-friendly institutions.

Game theoretic modeling and analysis : A co-evolutionary, agent-based approach

Ph.DDOCTOR OF PHILOSOPH

Learning and Co-operation in Mobile Multi-Robot Systems

Merged with duplicate record 10026.1/1984 on 27.02.2017 by CS (TIS)This thesis addresses the problem of setting the balance between exploration and exploitation in teams of learning robots who exchange information. Specifically it looks at groups of robots whose tasks include moving between salient points in the environment. To deal with unknown and dynamic environments,such robots need to be able to discover and learn the routes between these points themselves. A natural extension of this scenario is to allow the robots to exchange learned routes so that only one robot needs to learn a route for the whole team to use that route. One contribution of this thesis is to identify a dilemma created by this extension: that once one robot has learned a route between two points, all other robots will follow that route without looking for shorter versions. This trade-off will be labeled the Distributed Exploration vs. Exploitation Dilemma, since increasing distributed exploitation (allowing robots to exchange more routes) means decreasing distributed exploration (reducing robots ability to learn new versions of routes), and vice-versa. At different times, teams may be required with different balances of exploitation and exploration. The main contribution of this thesis is to present a system for setting the balance between exploration and exploitation in a group of robots. This system is demonstrated through experiments involving simulated robot teams. The experiments show that increasing and decreasing the value of a parameter of the novel system will lead to a significant increase and decrease respectively in average exploitation (and an equivalent decrease and increase in average exploration) over a series of team missions. A further set of experiments show that this holds true for a range of team sizes and numbers of goals

Analyzing Brain Networks Associated with Social Evaluation and Uncertainty in Subclinical Social Anxiety

In interpersonal interactions, socially anxious individuals continuously monitor for social threats and fear negative evaluation from their peers. We know little about whether these cognitive biases correlate with patterns of brain function in relevant regions that have been associated with evaluation of self and others. Recent evidence implicates neural structures critical to perspective-taking and the processing of uncertainty may function atypically in those who are anxious. In the present study, we examined neural activity in two such regions of the brain—the temporoparietal junction and the anterior midcingulate cortex — during Prisoner’s Dilemma game play. There were no significant group differences in activation in both regions during the processing of partner choice and anticipation of outcome during gameplay. However, there were significant differences in the processing of social feedback. These findings provide evidence that Prisoner’s Dilemma researchers should begin to consider how social and monetary context affects decision-making in diverse populations

Computing and evolving variants of computational depth

The structure and organization of information in binary strings and (infinite) binary sequences are investigated using two computable measures of complexity related to computational depth. First, fundamental properties of recursive computational depth, a refinement of Bennett\u27s original notion of computational depth, are developed, and it is shown that the recursively weakly (respectively, strongly) deep sequences form a proper subclass of the class of weakly (respectively, strongly) deep sequences. It is then shown that every weakly useful sequence is recursively strongly deep, strengthening a theorem by Juedes, Lathrop, and Lutz. It follows from these results that not every strongly deep sequence is weakly useful, thereby answering an open question posed by Juedes;Second, compression depth, a feasibly computable depth measurement, is developed based on the Lempel-Ziv compression algorithm. LZ compression depth is further formalized by introducing strongly (compression) deep sequences and showing that analogues of the main properties of computational depth hold for compression depth. Critical to these results, it is shown that a sequence that is not normal must be compressible by the Lempei-Ziv algorithm. This yields a new, simpler proof that the Champernowne sequence is normal;Compression depth is also used to measure the organization of genes in genetic algorithms. Using finite-state machines to control the actions of an automaton playing prisoner\u27s dilemma, a genetic algorithm is used to evolve a population of finite-state machines (players) to play prisoner\u27s dilemma against each other. Since the fitness function is based solely on how well a player performs against all other players in the population, any accumulation of compression depth (organization) in the genetic structure of the player can only by attributed to the fact that more fit players have a more highly organized genetic structure. It is shown experimentally that this is the case

The role of dysfunctional expectation persistence in psychopathology

In the literature, expectations are seen as core elements influencing and directing human behavior. There are many different models underlying this, such as the well-known expectancy–value theories. The past few decades have seen increased interest in analyzing the role of these theories in psychotherapy. On one hand, scholars have found increasingly convincing evidence of the impact of expectations on treatment success (i.e., placebo-effect research). On the other hand, the question has arisen whether people with mental disorders differ in the content of their expectations as well as in their processing mechanisms. The ViolEx model is one of the first expectation models that has been applied to the mechanisms of psychopathology and psychotherapy. It appears that people with mental disorders not only show a greater amount of dysfunctional expectations but also that those expectations are more persistent than in people without a mental disorder. In addition to other mechanisms, the concept of “cognitive immunization” has been suggested as responsible for the maintenance of dysfunctional expectations. First, researchers have found evidence for the link between cognitive immunization (i.e., expectation persistence after an expectation-disconfirming experience) and psychopathology. For this dissertation, the process of cognitive immunization, as a relatively new concept, was analyzed in detail, with the goal of developing interventions and reducing cognitive immunization processes. In the first study, the concept of cognitive immunization was analyzed in an experimental design (N = 102). Social expectations were induced and violated, and the expectation adaptation was hypothesized to differ between micro-interventions, including an expectation- focused psychological intervention (EFPI). The EFPI group showed significantly greater variability in their expectations and, thus, lower rates of cognitive immunization compared to the other groups. Second, the complexity of the implicit operationalization of cognitive immunization through experimental designs showed the need for efficient (self-rating) instruments. Therefore, a self-rating questionnaire, the Immunization Scale (IMS), has been developed. The IMS was validated through exploratory (N = 230) and confirmatory (N = 299) factor analyses, resulting in a 23-item questionnaire. In the third study, the EFPI was tested for its effectiveness in reducing cognitive immunization, measured with the IMS. Therefore, an online longitudinal randomized controlled design was developed for people with mild depressive and/or anxiety symptoms (N = 128). Cognitive immunization was correlated with psychopathology, and the EFPI group showed a significant reduction in the cognitive immunization level. Lastly, and based on the third study, a protocol paper was written for a large-scale psychotherapeutic study that analyzes the effectiveness of cognitive behavioral therapy (CBT) with the integration of EFPIs in people with diagnosed depression compared to standard CBT without special focus on expectations. This dissertation provides a validated questionnaire to analyze cognitive immunization processes and their link to psychopathology. It offers initial evidence of EFPIs’ effectiveness in reducing cognitive immunization in people with psychopathological symptoms. Practical and research implications are discussed

Altruistically Inclined?: The Behavioral Sciences, Evolutionary Theory, and the Origins of Reciprocity

Altruistically Inclined? examines the implications of recent research in the natural sciences for two important social scientific approaches to individual behavior: the economic/rational choice approach and the sociological/anthropological. It considers jointly two controversial and related ideas: the operation of group selection within early human evolutionary processes and the likelihood of modularity—domain-specific adaptations in our cognitive mechanisms and behavioral predispositions. Experimental research shows that people will often cooperate in one-shot prisoner\u27s dilemma (PD) games and reject positive offers in ultimatum games, contradicting commonly accepted notions of rationality. Upon first appearance, predispositions to behave in this fashion could not have been favored by natural selection operating only at the level of the individual organism. Emphasizing universal and variable features of human culture, developing research on how the brain functions, and refinements of thinking about levels of selection in evolutionary processes, Alexander J. Field argues that humans are born with the rudiments of a PD solution module—and differentially prepared to learn norms supportive of it. His emphasis on failure to harm, as opposed to the provision of affirmative assistance, as the empirically dominant form of altruistic behavior is also novel. The point of departure and principal point of reference is economics. But Altruistically Inclined? will interest a broad range of scholars in the social and behavioral sciences, natural scientists concerned with the implications of research and debates within their fields for the conduct of work elsewhere, and educated lay readers curious about essential features of human nature.https://scholarcommons.scu.edu/faculty_books/1325/thumbnail.jp

Understanding responses to environments for the Prisoner's Dilemma: A meta analysis, multidimensional optimisation and machine learning approach

This thesis investigates the behaviour that Iterated Prisoner’s Dilemma strategies should adopt as a response to different environments. The Iterated Prisoner’s Dilemma (IPD) is a particular topic of game theory that has attracted academic attention due to its applications in the understanding of the balance between cooperation and com petition in social and biological settings. This thesis uses a variety of mathematical and computational fields such as linear al gebra, research software engineering, data mining, network theory, natural language processing, data analysis, mathematical optimisation, resultant theory, markov mod elling, agent based simulation, heuristics and machine learning. The literature around the IPD has been exploring the performance of strategies in the game for years. The results of this thesis contribute to the discussion of successful performances using various novel approaches. Initially, this thesis evaluates the performance of 195 strategies in 45,600 computer tournaments. A large portion of the 195 strategies are drawn from the known and named strategies in the IPD literature, including many previous tournament winners. The 45,600 computer tournaments include tournament variations such as tournaments with noise, probabilistic match length, and both noise and probabilistic match length. This diversity of strategies and tournament types has resulted in the largest and most diverse collection of computer tournaments in the field. The impact of features on the performance of the 195 strategies is evaluated using modern machine learning and statistical techniques. The results reinforce the idea that there are properties associated with success, these are: be nice, be provocable and generous, be a little envious, be clever, and adapt to the environment. Secondly, this thesis explores well performed behaviour focused on a specific set of IPD strategies called memory-one, and specifically a subset of them that are considered extortionate. These strategies have gained much attention in the research field and have been acclaimed for their performance against single opponents. This thesis uses mathematical modelling to explore the best responses to a collection of memory-one strategies as a multidimensional non-linear optimisation problem, and the benefits of extortionate/manipulative behaviour. The results contribute to the discussion that behaving in an extortionate way is not the optimal play in the IPD, and provide evidence that memory-one strategies suffer from their limited memory in multi agent interactions and can be out performed by longer memory strategies. Following this, the thesis investigates best response strategies in the form of static sequences of moves. It introduces an evolutionary algorithm which can successfully identify best response sequences, and uses a list of 192 opponents to generate a large data set of best response sequences. This data set is then used to train a type of recurrent neural network called the long short-term memory network, which have not gained much attention in the literature. A number of long short-term memory networks are trained to predict the actions of the best response sequences. The trained networks are used to introduce a total of 24 new IPD strategies which were shown to successfully win standard tournaments. From this research the following conclusions are made: there is not a single best strategy in the IPD for varying environments, however, there are properties associated with the strategies’ success distinct to different environments. These properties reinforce and contradict well established results. They include being nice, opening with cooperation, being a little envious, being complex, adapting to the environment and using longer memory when possible