The “self-bad, partner-worse” strategy inhibits cooperation in networked populations

The emergence and maintenance of cooperation is a popular topic in studies of information sciences and evolutionary game theory. In two-player iterated games, memory in terms of the outcome of previous interactions and the strategy choices of co-players are of great referential significance for subsequent strategy actions. It is generally recognized that there is no single simple and overarching strategy whereby one player X can unilaterally achieve a higher payoff than his opponent Y, irrespective of Y's strategy and response. In this paper, we demonstrate that such strategies do exist in diverse networked populations. More precisely, (i) such strategies can obtain a low payoff for the focal player, however, they also lead to an even lower payoff for that player's partner, in turn lowering benefits of the overall populations; (ii) they are capable of winning with a high probability against opponents with an unknown strategy; and (iii) they have a survival advantage and robust fitness in terms of evolutionary processes. We refer to these as the “self-bad, partner-worse” (SBPW) strategies. Results presented here add to previous studies on strategy evolution in the context of social dilemmas and hint at some insights concerning cooperation promotion mechanisms among networked populations

Game Design: Competitive Mobile Games

This thesis explores the design process for a competitive multiplayer game mode in “baldorf,” a ball-throwing mobile game developed by Mystic Rhoads Productions. The research aims to enhance the overall gaming experience by introducing a competitive mode that challenges players’ skills and facilitates interaction with others. The research methodology included reviewing the popular competitive mobile games: Marvel Snap, Clash Royale, and Clash of Clans, which boast high download numbers and chart rankings. This analysis helped identify key features and mechanics that contribute to an engaging multiplayer experience. As a result, several designs were proposed, covering the profile, matchmaking, match, and leaderboard screens. These designs, created using the Figma mockup design tool, provided comprehensive descriptions of each feature and its in-game appearance. Additional features proposed in this thesis include synchronous play, a time limit for turns, forfeit options, summaries of turns and matches, live spectating, emotes, replays, and a match log. Collectively, these features and designs aim to provide a compelling and enjoyable competitive multiplayer mode for the game “baldorf.” The thesis concludes by discussing multiple directions for future research in this area, including more features, implementation, and monetization

Network Narrative: Prose Narrative Fiction and Participatory Cultural Production in Digital Information and Communication Networks

In this study of prose narrative created explicitly for participatory network communications environments I argue that network narratives constitute an important, born-networked form of literary and cultural expression. In the first half of the study I situate network narratives within a rich, dynamic process of reciprocity and codependence between the technological, material and formal properties of communication media on the one hand, and the uses of these media in cultural practices and forms of expression on the other. I point out how the medial and cultural flows that characterize contemporary network culture promote a codependent relation between narrative and information. This relation supports literary cultural expressions that invoke everyday communication practices increasingly shaped by mobile, networked computing devices. In the second half of this study, I extend theoretical work in the field of electronic literature and digital media to propose a set of four characteristics through which network narratives may be understood as distinct modes of networked, literary cultural expression. Network narratives, I suggest, are multimodal, distributed, participatory, and emergent. These attributes are present in distinct ways, within distinct topological layers of the narratives: in the story, discourse, and character networks of the narrative structure; in the formal and navigational structures; and in the participatory circuits of production, circulation and consumption. Attending to these topological layers and their interrelationships by using concepts derived from graph theory and network analysis offers a methodology that links the particular, closely read attributes and content of network narratives to a more distant understanding of changing patterns in broader, networked cultural production. Finally, I offer readings of five examples of network narratives. These include Kate Pullinger and Chris Joseph’s Flight Paths, Penguin Books and De Montfort University’s collaborative project A Million Penguins, the Apple iOS application The Silent History, Tim Burton’s collaboration with TIFF, BurtonStory, and a project by NFB Interactive, Out My Window. Each of these works incorporates user participation into its production circuits using different strategies, each with different implications for narrative and navigational structures. I conclude by describing these distinct strategies as additive participation – participation that becomes embedded within the work itself – and delineating different approaches that are employed independently or in combination by the authors and producers

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Deep learning for procedural content generation

Summarization: Procedural content generation in video games has a long history. Existing procedural content generation methods, such as search-based, solver-based, rule-based and grammar-based methods have been applied to various content types such as levels, maps, character models, and textures. A research field centered on content generation in games has existed for more than a decade. More recently, deep learning has powered a remarkable range of inventions in content production, which are applicable to games. While some cutting-edge deep learning methods are applied on their own, others are applied in combination with more traditional methods, or in an interactive setting. This article surveys the various deep learning methods that have been applied to generate game content directly or indirectly, discusses deep learning methods that could be used for content generation purposes but are rarely used today, and envisages some limitations and potential future directions of deep learning for procedural content generation.Presented on: Neural Computing and Application

Structural power and the evolution of collective fairness in social networks

From work contracts and group buying platforms to political coalitions and international climate and economical summits, often individuals assemble in groups that must collectively reach decisions that may favor each part unequally. Here we quantify to which extent our network ties promote the evolution of collective fairness in group interactions, modeled by means of Multiplayer Ultimatum Games (MUG). We show that a single topological feature of social networks-which we call structural power-has a profound impact on the tendency of individuals to take decisions that favor each part equally. Increased fair outcomes are attained whenever structural power is high, such that the networks that tie individuals allow them to meet the same partners in different groups, thus providing the opportunity to strongly influence each other. On the other hand, the absence of such close peer-influence relationships dismisses any positive effect created by the network. Interestingly, we show that increasing the structural power of a network leads to the appearance of well-defined modules-as found in human social networks that often exhibit community structure-providing an interaction environment that maximizes collective fairness.This research was supported by Fundacao para a Ciencia e Tecnologia (FCT) through grants SFRH/BD/94736/2013, PTDC/EEI-SII/5081/2014, PTDC/MAT/STA/3358/2014 and by multi-annual funding of CBMA and INESC-ID (under the projects UID/BIA/04050/2013 and UID/CEC/50021/2013) provided by FCT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Utopias and Dystopias as Cybernetic Information Systems: Envisioning the Posthuman Neuropolity

While it is possible to understand utopias and dystopias as particular kinds of sociopolitical systems, in this text we argue that utopias and dystopias can also be understood as particular kinds of information systems in which data is received, stored, generated, processed, and transmitted by the minds of human beings that constitute the system’s ‘nodes’ and which are connected according to specific network topologies. We begin by formulating a model of cybernetic information-processing properties that characterize utopias and dystopias. It is then shown that the growing use of neuroprosthetic technologies for human enhancement is expected to radically reshape the ways in which human minds access, manipulate, and share information with one another; for example, such technologies may give rise to posthuman ‘neuropolities’ in which human minds can interact with their environment using new sensorimotor capacities, dwell within shared virtual cyberworlds, and link with one another to form new kinds of social organizations, including hive minds that utilize communal memory and decision-making. Drawing on our model, we argue that the dynamics of such neuropolities will allow (or perhaps even impel) the creation of new kinds of utopias and dystopias that were previously impossible to realize. Finally, we suggest that it is important that humanity begin thoughtfully exploring the ethical, social, and political implications of realizing such technologically enabled societies by studying neuropolities in a place where they have already been ‘pre-engineered’ and provisionally exist: in works of audiovisual science fiction such as films, television series, and role-playing games

Spatial-temporal reasoning applications of computational intelligence in the game of Go and computer networks

Spatial-temporal reasoning is the ability to reason with spatial images or information about space over time. In this dissertation, computational intelligence techniques are applied to computer Go and computer network applications. Among four experiments, the first three are related to the game of Go, and the last one concerns the routing problem in computer networks. The first experiment represents the first training of a modified cellular simultaneous recurrent network (CSRN) trained with cellular particle swarm optimization (PSO). Another contribution is the development of a comprehensive theoretical study of a 2x2 Go research platform with a certified 5 dan Go expert. The proposed architecture successfully trains a 2x2 game tree. The contribution of the second experiment is the development of a computational intelligence algorithm calledcollective cooperative learning (CCL). CCL learns the group size of Go stones on a Go board with zero knowledge by communicating only with the immediate neighbors. An analysis determines the lower bound of a design parameter that guarantees a solution. The contribution of the third experiment is the proposal of a unified system architecture for a Go robot. A prototype Go robot is implemented for the first time in the literature. The last experiment tackles a disruption-tolerant routing problem for a network suffering from link disruption. This experiment represents the first time that the disruption-tolerant routing problem has been formulated with a Markov Decision Process. In addition, the packet delivery rate has been improved under a range of link disruption levels via a reinforcement learning approach --Abstract, page iv

An inertial motion capture framework for constructing body sensor networks

Motion capture is the process of measuring and subsequently reconstructing the movement of an animated object or being in virtual space. Virtual reconstructions of human motion play an important role in numerous application areas such as animation, medical science, ergonomics, etc. While optical motion capture systems are the industry standard, inertial body sensor networks are becoming viable alternatives due to portability, practicality and cost. This thesis presents an innovative inertial motion capture framework for constructing body sensor networks through software environments, smartphones and web technologies. The first component of the framework is a unique inertial motion capture software environment aimed at providing an improved experimentation environment, accompanied by programming scaffolding and a driver development kit, for users interested in studying or engineering body sensor networks. The software environment provides a bespoke 3D engine for kinematic motion visualisations and a set of tools for hardware integration. The software environment is used to develop the hardware behind a prototype motion capture suit focused on low-power consumption and hardware-centricity. Additional inertial measurement units, which are available commercially, are also integrated to demonstrate the functionality the software environment while providing the framework with additional sources for motion data. The smartphone is the most ubiquitous computing technology and its worldwide uptake has prompted many advances in wearable inertial sensing technologies. Smartphones contain gyroscopes, accelerometers and magnetometers, a combination of sensors that is commonly found in inertial measurement units. This thesis presents a mobile application that investigates whether the smartphone is capable of inertial motion capture by constructing a novel omnidirectional body sensor network. This thesis proposes a novel use for web technologies through the development of the Motion Cloud, a repository and gateway for inertial data. Web technologies have the potential to replace motion capture file formats with online repositories and to set a new standard for how motion data is stored. From a single inertial measurement unit to a more complex body sensor network, the proposed architecture is extendable and facilitates the integration of any inertial hardware configuration. The Motion Cloud’s data can be accessed through an application-programming interface or through a web portal that provides users with the functionality for visualising and exporting the motion data