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    • Agent based modeling ABM is an

    2018-10-29

    Agent based modeling (ABM) is an emerging approach to modeling complex processes and phenomena in social science in recent years. Also recognized as multi-agent system (MAS), agent based simulation (ABS), or individual based modeling (IBM), its origin can be traced back to as early as the 1940s when the first prototypical “cellular automata” was invented simulating grids\' interaction with their immediate neighbors by on–off state switches (e.g. Von Neumann, 1951, Fig.1(a)). Computer simulation of agents was revolutionized by Reynolds (1987) by introducing individual perception, intelligence and behavior to his Boids agents, and therefore allowing emergent pattern based on a large group of constituent units to be simulated (Fig.1(b)). Despite its long history, it fexofenadine hydrochloride is only until the 1990s has the agent modeling paradigm become both computationally and conceptually mature to be employed as a feasible simulation tool and sparked interest from the social science and the so-called urban analysis community. For the last two decades or so, ABM has been widely applied in studies along this line. As Wooldridge put it: “There was a time when I rather arrogantly believed I had read all the key papers in the multi-agent systems field, and had a basic working knowledge of all the main research problems and techniques. Well, if that was ever true, then it certainly isn\'t any more, and hasn\'t been for nearly two decades: the time has long since passed when any one individual could have a deep understanding of the entire multi-agent systems research area.” (Wooldridge, 2009, p. xix) This paper does not seek to provide a complete review of such broad literature. Rather, it takes a much less ambitious goal and aims to depict how ABM has been adapted by researchers in urban and architectural studies as their conceptual paradigm as well as instrumental device, and gives a brief review of ABM research from both theoretical and practical aspects in these fields. An up-to-date bibliography is also provided.
    ABM: definition and features Being the basic, and the most essential unit of agent-based models, perhaps the concept of agent should be defined in the first place before we embark on further review. Unfortunately, despite its common usage, there is no single universally accepted definition of what an agent is. Actually there has been a great deal of debate on this very subject (Franklin and Graesser, 1997; Müller et al., 1995), and the existing definitions of agent are many and various, ranging from as primitive and loose as an individual agent is “just something that perceives and acts” (Russell and Norvig, 1995, p. 7), to as elaborate and rigorous as “Autonomous agents are computational systems that inhabit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks for which they are designed.” (Maes, 1995). In attempting to avoid prescriptive arguments in the controversy, Russell and Norvig (1995, p. 33) put: “The notion of an agent is meant to be a tool for analyzing systems, not an absolute characterization that divides the world into agents and non-agents.” Nevertheless, a definition of agents, as what fontanels is and what it does, will at least avoid confusion and suffice the discussion, and therefore is presented below. Wooldridge and Jennings (1995) summarized the features of agents as autonomy, social ability, reactivity and pro-activeness, and in their later work formalized the definition of agent in a comprehensive as well as succinct way, stating: This definition emphasizes on the two central properties of agents that have been commonly agreed on by people working in related areas: autonomy and social ability. Being autonomous means that an agent must be able to operate, carry out instructions and make decisions without direct intervention of others, and have control over their actions and internal state (Castelfranchi, 1995; Hayes, 1999); being social means that an agent is part of a community, being able to interact with other agents in order to complete their own tasks and to help others with their activities (Genesereth and Ketchpel, 1994; Hayes, 1999; Jennings et al., 1998). These two key properties together distinguish agent-based system from related software paradigms such as object-oriented programming and distributed computation. A discussion of agent-based system in the pure context of software engineering is given in (Wooldridge, 1997). A sketch depicting the relationship between an agent and its environment is shown in Fig. 2.