Communities of Play: Emergent Cultures in Online Games and Virtual Worlds
Games as Emergent, Complex Systems
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Games as Emergent, Complex SystemsThe conception of games as complex systems with emergent properties is so prevalent in the discourse of both game design and game studies that it would be impossible to cite its origins. Descriptions of emergence can be found in a diverse array of contexts, from books on “popular science” (Johnson 2001) to “game design theory” (Juul 2002; Salen and Zimmerman 2004). So what, precisely, do we mean by “emergence?” Emergence is a phenomenon comes out of the study of “complex systems” or “complexity theory,” another area that also serves as a fulcrum for interdisciplinary research. The Santa Fe Institute, one of the preeminent centers for the study of complex systems in the United States, encompasses fields as diverse as social science, economics, mathematics, game theory (a branch of applied mathematics and economics unrelated to “game studies”), ecology, evolution, the environment, organization and management, neuroscience, intelligent systems and network infrastructures. (REF: SFI web site) The Human Complex Systems group at University of California Los Angeles embraces every permutation of its theme, from economics to urban planning and computer-generated “synthetic cultures,” to multiplayer online games. (REF: HCS web site) The term “emergence” describes how complex, often decentralized, systems self-organize in ways that cannot be predicted by their underlying structures or rule sets, nor by the individual behavior of agents within the system (Bar-Yam 1997). Anthills, freeways, neural networks, stock markets, terrorist cells, cities, the internet and computer games are examples used to describe emergence (Johnson 2001). These disparate systems share in common a display of collective behaviors and even collective “intelligences” that arise out of, and yet transcend the actions of the individual parts or elements. According to Steven Johnson, author of Emergence: The Connected Lives of Ants, Brains, Cities and Software, complex systems exhibit emergence because they …solve problems by drawing on masses of relatively (simple) elements, rather than a single, intelligent “executive branch.” They are bottom-up systems, not top-down. They get their smarts from below. In more technical language, they are complex adaptive systems that display emergent behavior. In these systems, agents residing on one scale start producing behavior that lies one scale above them: ants create colonies; urbanities create neighborhoods; simple pattern-recognition software learns how to recommend new books. The movement from low-level rules to higher-level sophistication is what we call emergence. (Johnson 2001, p. #) It is significant that one of the key characters Johnson features his discussion of emergence in all its permutations is Will Wright, designer of the games SimCity, The Sims and The Sims Online, and games make repeated appearances throughout the book. The notion of emergence as a property of games is pervasive. Media scholar Janet Murray has described one of the properties of computational media as being “procedural,” or rule-based. Rule-based systems have a greater tendency towards emergence because they have a larger possibility space with affordances for more varied outcomes. Even simple rules systems can produce complex, emergent outcomes. Using examples of board games, sports, most action games and all strategy games, “Ludologist” Jesper Juul argues that emergence is “the primordial game structure, where a game is specified as a small number of rules that yield large numbers of game variations, that the players must design strategies for dealing with.” “Progression” he describes as “the historically newer structure” in which we find “cinematic storytelling ambitions” in this otherwise indigenously procedural and hence emergent medium (Juul 2002; Juul 2004) (REF p#). In Rules of Play, Salen and Zimmerman look in-depth at notions of games as complex systems and emergence as an outcome of the interaction of rules. (Salen and Zimmerman 2004) In my 2002 paper on emergent authorship, I describe a new model for storytelling in which players themselves contribute to narratives in games such as The Sims, Ultima Online and EverQuest through emergent processes. (REF: Pearce 2002) Cindy Poremba’s Master’s thesis provided a further analysis of the player as co-creator within the context of these emergent story systems. (REF: Poremba thesis) These ideas parallel Henry Jenkins’ notion of “textual poaching,” in which fan cultures, such as Star Trek fans, aka “Trekkies,” develop their own emergent narratives from the kit of parts provided by the television series. (REF: Jenkins 1992) So what, precisely, is emergence, and how might it be studied? In his essay for the book Virtual Worlds: Synthetic Universes, Digital Life and Complexity, Yaneer Bar-Yam, President of the New England Complex Systems Institute, defines emergence as a set of “collective behaviors” in which all the parts are “interdependent,” arguing that the more distinct and specialized the individual interdependent behaviors, the more complex the collective behavior likely to arise (Bar-Yam 1999). Bar-Yam describes emergence as
Further:
(REF: Page #) In discussing methodology, Bar-Yam suggests a holistic approach to observing the relationship between the parts and the system as a whole: …emergent properties cannot be studied by physically taking a system apart and looking at the parts (reductionism). They can, however, be studied by looking at each of the parts in the context of the system as a whole. This is the nature of emergence and an indication of how it can be studied and understood. (Bar-Yam 1997) (REF: page #) To describe this process, Bar-Yam invokes the metaphor of “[seeing] the forest and the trees at the same time... We see the ways the trees and the forest are related to each other” (Bar-Yam 2000b, p.#). Sociologist C. Wright Mills has drawn upon the same metaphor to describe the essential character of what he calls “the sociological imagination” (Mills 1959) This apt metaphor illustrates the key challenge of studying emergence in large-scale social systems. This type of research necessitates a methodology that enables one to observe and analyze phenomena at different scales simultaneously. In other words, it must enable us to look at the behavior of individual units in a complex system, their relationship to each other, and the overarching patterns of the system as whole, all at the same time. We cannot, as De Landa has pointed out, calculate the patterns within a complex system by the reductionist method of studying the properties of its parts. It is also crucial to be able to observe the system’s dynamics, as well as their outcomes, in progress. Capturing their evidence exclusively after the fact, either through surveys or forensic evidence, such as artifacts, will not allow a complete understanding of patterns of emergence. In addition, we are faced with the problem of observing the relationship between the play community and the play ecosystem, which can only really be understood as a lived practice. As Bar-Yam points out, “One of the problems in thinking about the concepts of complex systems is that we often assign properties to a system that are actually properties of a relationship between the system and its environment.” (REF: p#) This is particularly significant to the research described here, where relationships between players, as well as the players’ relationship to the environment of the virtual world, are central: “When parts of a system are related to each other, we talk about them as a network, when a system is related to parts of a larger system, we talk about its ecosystem.” (Bar-Yam 2000a, p.#) Returning to our earlier discussion placing MMOWs along a spectrum of “fixed synthetic” versus “co-created worlds,” we can begin to look at these environments as “play ecosystems” in which “networks” of players engage in various emergent behaviors. This is where the distinctions between different types of worlds become important: each ecosystem provides particular designed characteristics and affordances which affect the emergent behavior of networks within it. As we shall see, a play community can exhibit patterns of emergence that transcend any particular virtual world, but these are made explicit through interactions unique to the affordances of each play ecosystem. One of the critical properties of complex systems is feedback. In cybernetics, feedback is defined as a phenomenon in which some portion of the output of a system is passed through the input. This can be used to describe machines that utilize feedback systems, the classic example being a thermostat on a heater (REF). The thermostat continually reads the temperature and makes adjustments accordingly. Within networked social systems, feedback can be a powerful engine for large-scale social emergence, and the accelerated forms of emergence seen in these systems are a direct result of the designed affordances of the software. Examples of this on the Internet include iTunes, MySpace and YouTube, each of which has grown exponentially since its inception through feedback. This process, epitomized by YouTube, can be described thus: the more people who watch, the more people who upload videos; the more people who upload videos, the more people who watch. Networks are particularly good at processing feedback since many units of input can move quickly through the system and be distributed to a large number of outputs. This research concerns the ways in which both the social context of play and the design of the game software itself facilitate this feedback process. The qualities of properties of play are critical. Play can be viewed as a particular type of engine for emergence by virtue of its feedback dynamics. Play is inherently spontaneous and experimental, and therefore, players will find themselves responding to social feedback in a very different way than they might in other contexts. The common types of emergence seen within virtual multiplayer games and virtual worlds illustrate this point. As we’ve seen, they include online weddings, game-wide protests, social organizations such as guilds or social groups, various types of social and fashion trends, and extra-virtual phenomena such as fan sites and selling of virtual characters, items or currency. The “play frame” sets the stage for many of these phenomena, but the virtual environments themselves also have particular properties that lend themselves to emergence:
One of the challenges of studying emergent behavior is that we sometimes only know it by its forensic evidence. We know, for instance, that thousands of players abandoned The Sims Online, but we do not have any way to understand what happened after the fact. In addition, emergence often happens at such a large scale that it is very difficult to observe in any meaningful way, other than in terms of demographics or quantitative data. So the challenge here was to identify a subject that met all the criteria for emergence, but was imminently studyable. The Uru group fit this criteria for the following reasons:
A methodological conundrum confronts us at this point. What tools and methods shall we use to observe the emergent phenomena we have defined here? There are a number of different established methods in game studies. Quantitative methods, such as surveys, and in-game data mining can provide us with very useful information; they are excellent at understanding the scope of individuals’ attitudes about their gameplay experience. They are also effective at getting at the larger patterns of behavior and attitudes displayed by individuals. Quantitative methods are, however, less effective at getting at larger patterns of interaction between individuals. Large-scale surveys help us understand that people are spending an average of 20 hours a week in online games, but not specifically what they are doing, who they are spending time with, and how they interact in social contexts within the ecosystem. Data mining, such as capturing chatlogs in a fixed location, is an excellent method for discourse analysis in specific contexts, although it does not give us the attitudinal data of surveys, nor measure larger cultural patterns across multiple locations. Social network theory, used extensively in Internet Studies and computer-mediated communications, branches of sociology, and organizational theory, provides excellent methods for understanding the movement of information and the overall structures of social networks. Yet it lacks the tools we need to study the intersubjective social transactions of meaning-making from which cultures are constructed. Thus we need to identify a method that is particularly strong at analyzing and interpreting the dynamics and formation of culture. Download 0.83 Mb. Share with your friends:
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