THE EFFECTS OF FEEDBACK ON COOPERATION IN THE PRISONER’S DILEMMA GAME SIMULATING A CLOSED MARKET SCENARIO

This study explores the effects of feedback on cooperation in the iterated prisoner’s dilemma game (PDG). Four sources of feedback were identified: peer, buyer, market and cultural feedback. Peer and buyer feedback were intrinsic to the PDG, for they were analyzed, but not manipulated. Market and cultural feedback comprised independent variables and their effects were measured on players’ and group cooperation (dependent variables). Twenty-seven participants played a PDG, divided in 9 groups of 3 players each. Cooperation was measured as rates of individual players’ cooperative X choices, and as aggregate products within groups. At the molecular (moment-to-moment) level, there was a significant within-subjects main effect of the market feedback F(1, 28) = 6.50, p = .02, ?p2 = .19. At the molar level, there was no significant effect of the market feedback, nor of the cultural feedback. It was not possible to establish a metacontingency between recurrent group cooperation and positive contingent group consequences. Players displayed sub-optimal choice behavior, seeking to maximize relative earnings within their group (defecting) over absolute earnings (cooperating). These results are discussed in light of how the source of feedback may sustain cooperation or defection in the PDG, and their implications in organizational settings. Reinforcing cooperative behaviors can be key to the maintenance and development of any organization, for informative performance feedback may not suffice. This study contributes to the understanding of economic decisional behavior in groups from a cultural selectionist perspective.Keywords: choice, cooperation, feedback, metacontingency, prisoner’s dilemma gameThis study explores the effects of feedback on cooperation in the iterated prisoner’s dilemma game (PDG). Four sources of feedback were identified: peer, buyer, market and cultural feedback. Peer and buyer feedback were intrinsic to the PDG, for they were analyzed, but not manipulated. Market and cultural feedback comprised independent variables and their effects were measured on players’ and group cooperation (dependent variables). Twenty-seven participants played a PDG, divided in 9 groups of 3 players each. Cooperation was measured as rates of individual players’ cooperative X choices, and as aggregate products within groups. At the molecular (moment-to-moment) level, there was a significant within-subjects main effect of the market feedback F(1, 28) = 6.50, p = .02, ?p2 = .19. At the molar level, there was no significant effect of the market feedback, nor of the cultural feedback. It was not possible to establish a metacontingency between recurrent group cooperation and positive contingent group consequences. Players displayed sub-optimal choice behavior, seeking to maximize relative earnings within their group (defecting) over absolute earnings (cooperating). These results are discussed in light of how the source of feedback may sustain cooperation or defection in the PDG, and their implications in organizational settings. Reinforcing cooperative behaviors can be key to the maintenance and development of any organization, for informative performance feedback may not suffice. This study contributes to the understanding of economic decisional behavior in groups from a cultural selectionist perspective.Keywords: choice, cooperation, feedback, metacontingency, prisoner’s dilemma gam

One Step at a Time: Does Gradualism Build Coordination?

We study how gradualism -- increasing required levels (“thresholds”) of contributions slowly over time rather than requiring a high level of contribution immediately -- affects individuals’ decisions to contribute to a public project. Using a laboratory binary choice minimum-effort coordination game, we randomly assign participants to three treatments: starting and continuing at a high threshold, starting at a low threshold but jumping to a high threshold after a few periods, and starting at a low threshold and gradually increasing the threshold over time (the “gradualism” treatment). We find that individuals coordinate most successfully at the high threshold in the gradualism treatment relative to the other two groups. We propose a theory based on belief updating to explain why gradualism works. We also discuss alternative explanations such as reinforcement learning, conditional cooperation, inertia, preference for consistency, and limited attention. Our findings point to a simple, voluntary mechanism to promote successful coordination when the capacity to impose sanctions is limited.Gradualism; Coordination; Cooperation; Public Goods; Belief-based Learning; Laboratory Experiment

I want it now so you cannot have it later: The role of impulsive choices in competitive environments

Doctor of PhilosophyDepartment of Psychological SciencesMichael YoungPeople commonly prefer smaller-sooner rewards over larger-later rewards, referred to as impulsive choice. Although impulsive choices are strongly associated with negative behaviors, such as poor diet and exercise habits, substance abuse and gambling, larger delayed rewards are more uncertain than smaller immediate rewards regarding if and when they are delivered. The threat of losing out on delayed rewards may then motivate individuals to shift their preferences towards more immediately available goals. One source of uncertainty for delayed rewards is competition, where multiple individuals exclusively pursue limited resources. The impact of competitors may result in individuals selecting more impulsive choices to ensure a relatively greater acquisition of important resources compared to competitors, despite the environment originally incentivizing waiting. Therefore, the purpose of the current dissertation is to study the degree to which competition-based uncertainty increases impulsive choices above and beyond environmental uncertainty. To test this hypothesis, I conducted two experience-based decision-making experiments that manipulated various dimensions of competition that could potentially control participants’ waiting behaviors and performance, such as the visibility of a competitor and the visibility of the competitor’s cumulative rewards. Overall, the results provided weak evidence that competition influenced participants’ impulsive choices above environmental uncertainty, specifically by slightly increasing their likelihood of obtaining rewards rather than their tendency to select impulsive choices. These findings are more consistent with an economic perspective of choice behavior than an evolutionary perspective, and I discuss the theoretical and methodological implications of this novel line of research

Defining the mechanisms of a cooperative computer system based on theories of cooperation

There is a growing interest in the development of computer systems that are actively involved in the tasks of the users and serve to augment the users' creativity. Cooperative computing is a major contribution to this research field. A survey of current developments in knowledge based systems led to the conclusion that there has hitherto been an absence of a formal definition of the mechanisms of cooperative computer systems based on theories of cooperation. The work in this thesis seeks to provide a full definition of cooperation derived from the behaviours of living cooperative systems. Studies on human cooperation and cooperation in the animal kingdom, established that cooperation is a dynamic behaviour; in that the interaction processes between the cooperative partners serve to facilitate the achievement of a common goal, or a set of goals that are mutually desired by the partners. Partners in cooperation are interdependent: one member's actions are contingent on another. Therefore, the underlying processes which induce and maintain cooperation were identified. These are: communication between the partners; emergence of norms and roles governing the behaviour of the cooperating members; resolution of conflicts; distributed and coordinated activities. These factors were further elucidated within the context of small problem solving groups. A model of cooperationw hich encapsulatedth esef actors was produced. From the discussionso f the advantageso f cooperationw ithin different contexts, the potential for synergy was found to be the main benefit of cooperation. The potential for achieving this synergy between a human and a computer is the main motivation for the work undertaken in this research. From the theoretical analysis of cooperation, the underlying mechanisms of a cooperative computer were successfully defined. A conceptual model of human-computer cooperation was presented. It was established that the quality of cooperation is closely associated with the nature of the task. Therefore, it is not practicable to produce a general purpose cooperative system. A specific task must be used. Creative tasks of a problem identifying and solving nature, were found to be more suitable to cooperative behaviour than others. Typical of these, and the one selected, was computer screen design. Current screen design practice was analysed, and the functional requirements and knowledge base needs of the systems were established. The underlying mechanisms of cooperation were formalised and successfully implemented within a software exemplar, named COSY. COSY exhibits the behavioural characteristics of cooperation, and utilises the knowledge of screen design to support users in the task of formatting computer screens. COSY successfully demonstrated the synergistic relationship in its cooperation with the users. It is concluded that the approach undertaken in this thesis has lead to a successful definition and implementation of the formal mechanisms of cooperation in a computer system, one which potentially enhances the innovative and creative aspects of design work

Individuals behaviour in social dilemma games and the role played by persuasion : theory and experiments.

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN042025 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Community cooperation and social solidarity: a case study of community initiated strategic planning

This research explored the process of creating a shared future and the evolution of cooperative collective endeavours in a regional rural community through a bottom-up planning process that involved professionals, public leadership and residents of a rural region in Israel. Using the MT rural region in Israel as a case study, the research was an interpretive exploration of how this community changed the way it collectively functions to achieve individual and shared aspirations. It examined how the community restructured its patterns of interaction, changing the social dynamics – which people interacted with each other, how they interacted with each other, and who felt committed to whom. The motivation for this inquiry stemmed from my desire as a practitioner to better understand the processes by which communities learn to function cooperatively. What are the elements that contributed to enabling a community to create the conditions for collectively utilizing and sustaining common resources rather than dividing them up for private consumption and exploitative narrow interests? What type of cooperative mechanisms enabled people to accomplish together what they cannot accomplish alone? Specifically, there are three research questions: how the change process was initiated in MT, what was significant in the nature of participation in the planning process, and how the mechanisms for regional community cooperation evolved. It was a case study of the planning and development process that I facilitated in MT from 1994-1999 (prior to my intention to undertake research) and is based mainly upon recent interviews of the participants (in that process), their recollections, and retrospective interpretations of that experience. The case has been explored from the theoretical perspective of viewing society in general, and community life in particular, as processes of constructing shared social realities that produce certain collective behaviours of cooperation or non-cooperation (Berger and Luckmann, 1967). This research was about understanding the process of making social rules that incorporate shared meanings and sanctions (Giddens, 1986) for undertaking joint endeavours (Ostrom, 1990, 1992, Wenger, 1998). Specifically two primary insights have come out of this case analysis: 1. In the MT case there was a mutually reinforcing three-way interplay between the strengthening of commitments to mutual care on the regional level, the instrumental benefits from cooperative/joint endeavours, and the envisioning of a shared future. 2. The community development process was owned by the community (not by outside agencies) and they (the community members) set the rules for community involvement. They structured the social interactions which formed the basis for creating shared understandings as a collective to achieve their common future. These insights shed light on how a community's structuring of its interactions and development interventions influenced its ability to act in a collectively optimal manner. By looking at the interrelation between trust as a function of social esteem (Honneth, 1995) and risk taking linked to instrumental benefits of cooperation (Lewis, 2002; Taylor, 1976; White, 2003) we can better understand what contributes to the way some communities continue to miss opportunities (Ostrom 1992), while others are able to promote their collective development and mutual wellbeing. By examining the process of designing (not only the design itself) community development programmes (Block, 2009) and by observing participation not as technique but as an inherent part of the way a community begins structuring its social interactions with their tacit (Polanyi, 1966) and explicit meanings, we can better understand the role of practitioners. And finally, perhaps the elements of chance and opportunity that bring certain combinations of people together in a given time and space may need to be given more weight in what remains a very unpredictable non-linear field of professional practice

Abstract and lifelike experimental games

The theory of games seems to me to provide the most promising alternative to the traditional theories of social behaviour. Gaming modelS are inherently social in character (an individual's strategy choice in a game cannot even be properly defined without reference to at least one other individual) and they represent a radical departure from the "social stimulus - individual response" approach. They sean, furthermore, to be the only models which can adequately conceptualize an important (and large) class of social behaviours which arise from deliberate free choice. (From preface

The future of decisions from experience : connecting real-world decision problems to cognitive processes

In many important real-world decision domains, such as finance, the environment, and health, behavior is strongly influenced by experience. Renewed interest in studying this influence led to important advancements in the understanding of these decisions from experience (DfE) in the last 20 years. Building on this literature, we suggest ways the standard experimental design should be extended to better approach important real-world DfE. These extensions include, for example, introducing more complex choice situations, delaying feedback, and including social interactions. When acting upon experiences in these richer and more complicated environments, extensive cognitive processes go into making a decision. Therefore, we argue for integrating cognitive processes more explicitly into experimental research in DfE. These cognitive processes include attention to and perception of numeric and nonnumeric experiences, the influence of episodic and semantic memory, and the mental models involved in learning processes. Understanding these basic cognitive processes can advance the modeling, understanding and prediction of DfE in the laboratory and in the real world. We highlight the potential of experimental research in DfE for theory integration across the behavioral, decision, and cognitive sciences. Furthermore, this research could lead to new methodology that better informs decision-making and policy interventions

Catgame: A Tool For Problem Solving In Complex Dynamic Systems Using Game Theoretic Knowledge Distribution In Cultural Algorithms, And Its Application (catneuro) To The Deep Learning Of Game Controller

Cultural Algorithms (CA) are knowledge-intensive, population-based stochastic optimization methods that are modeled after human cultures and are suited to solving problems in complex environments. The CA Belief Space stores knowledge harvested from prior generations and re-distributes it to future generations via a knowledge distribution (KD) mechanism. Each of the population individuals is then guided through the search space via the associated knowledge. Previously, CA implementations have used only competitive KD mechanisms that have performed well for problems embedded in static environments. Relatively recently, CA research has evolved to encompass dynamic problem environments. Given increasing environmental complexity, a natural question arises about whether KD mechanisms that also incorporate cooperation can perform better in such environments than purely competitive ones? Borrowing from game theory, game-based KD mechanisms are implemented and tested against the default competitive mechanism – Weighted Majority (WTD). Two different concepts of complexity are addressed – numerical optimization under dynamic environments and hierarchal, multi-objective optimization for evolving deep learning models. The former is addressed with the CATGame software system and the later with CATNeuro. CATGame implements three types of games that span both cooperation and competition for knowledge distribution, namely: Iterated Prisoner\u27s Dilemma (IPD), Stag-Hunt and Stackelberg. The performance of the three game mechanisms is compared with the aid of a dynamic problem generator called Cones World. Weighted Majority, aka “wisdom of the crowd”, the default CA competitive KD mechanism is used as the benchmark. It is shown that games that support both cooperation and competition do indeed perform better but not in all cases. The results shed light on what kinds of games are suited to problem solving in complex, dynamic environments. Specifically, games that balance exploration and exploitation using the local signal of ‘social’ rank – Stag-Hunt and IPD – perform better. Stag-Hunt which is also the most cooperative of the games tested, performed the best overall. Dynamic analysis of the ‘social’ aspects of the CA test runs shows that Stag-Hunt allocates compute resources more consistently than the others in response to environmental complexity changes. Stackelberg where the allocation decisions are centralized, like in a centrally planned economic system, is found to be the least adaptive. CATNeuro is for solving neural architecture search (NAS) problems. Contemporary ‘deep learning’ neural network models are proven effective. However, the network topologies may be complex and not immediately obvious for the problem at hand. This has given rise to the secondary field of neural architecture search. It is still nascent with many frameworks and approaches now becoming available. This paper describes a NAS method based on graph evolution pioneered by NEAT (Neuroevolution of Augmenting Topologies) but driven by the evolutionary mechanisms under Cultural Algorithms. Here CATNeuro is applied to find optimal network topologies to play a 2D fighting game called FightingICE (derived from “The Rumble Fish” video game). A policy-based, reinforcement learning method is used to create the training data for network optimization. CATNeuro is still evolving. To inform the development of CATNeuro, in this primary foray into NAS, we contrast the performance of CATNeuro with two different knowledge distribution mechanisms – the stalwart Weighted Majority and a new one based on the Stag-Hunt game from evolutionary game theory that performed the best in CATGame. The research shows that Stag-Hunt has a distinct edge over WTD in terms of game performance, model accuracy, and model size. It is therefore deemed to be the preferred mechanism for complex, hierarchical optimization tasks such as NAS and is planned to be used as the default KD mechanism in CATNeuro going forward