Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of “word of mouth ” in the promotion of new products. Recently, motivated by the design of viral marketing strategies, Domingos and Richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation, and the goal is to trigger a large cascade of further adoptions, which set of individuals should we target? We consider this problem in several of the most widely studied models in social network analysis. The optimization problem of selecting the most influential nodes is NP-hard here, and we provide the first provable approximation guarantees for efficient algorithms. Using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63 % of optimal for several classes of models; our framework suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks. We also provide computational experiments on large collaboration networks, showing that in addition to their provable guarantees, our approximation algorithms significantly out-perform nodeselection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks.

We study the problem of maximizing the expected spread of an innovation or behavior within a social network, in the presence of "word-of-mouth" referral. Our work builds on the observation that individuals' decisions to purchase a product or adopt an innovation are strongly influenced by recommendations from their friends and acquaintances. Understanding

In this paper, we review and analyze the emerging network paradigm in organizational research. We begin with a conventional review of recent research organized around recognized research streams. Next, we analyze this research, developing a set of dimensions along which network studies vary, including direction of causality, levels of analysis, explanatory goals, and explanatory mechanisms. We use the latter two dimensions to construct a 2-by-2 table cross-classifying studies of network consequences into four canonical types: structural social capital, social access to resources, contagion, and environmental shaping. We note the rise in popularity of studies with a greater sense of agency than was traditional in network research.

Contrary to cognitive approaches of agency where a lot of effort is devoted to the formalization of agent concepts, little work has been done on the formalization of situated multi-agent systems (situated MASs). In this paper we present a generic model for situated MASs. This model formally describes an abstract architecture for situated MASs. In this architecture each agent is situated in his local context that he is able to perceive and in which he can act. Since intelligence in situated MASs results from the interactions of agents with the environment rather than from their individual capabilities, the model takes an action-centric approach. The model deals with (1) the actions of agents in the environment, (2) ongoing activities in the environment, such as moving objects, and (3) the interactions between agents and ongoing activities through the environment. One model for

This article introduces a general sociological readership to multiagent systems (MAS), a new computer simulation technology that has increasingly been used to describe and explain sociological phenomena. The author uses the term artificial societies to refer to social simulations using MAS and he describes MAS technology and contrasts it with other social simulation technologies. The author argues that MAS have attained a level of maturity where they can be useful tools for sociologists, and he shows how MAS provide new perspectives on contemporary discussions of the micro-macro link in sociological theory by focusing on three aspects of the micro-macro link: micro-to-macro emergence, macro-to-micro social causation, and the dialectic between emergence and social causation.

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Abstract. In situated multi-agent systems (situated MASs), agents are explicitly placed in an environment. A situated agent does not not use long-term planning to decide what action sequence should be executed, but selects actions on the basis of its current position, the world it perceives and limited internal state. Situated agents exploit the environment to coordinate their behavior and to reach a common goal. In a recent project, we applied situated MASs to the control of an automated transportation system that uses automatic guided vehicles (AGVs) to transport loads in a warehouse. In contrast to traditional approaches where the AGVs are controlled by a central server, in this project we model the AGVs as agents in a situated MAS, aiming to improve flexibility and openness. Since the physical environment of AGVs is very restricted, it offers little opportunities for agents to use the environment. We introduce a virtual environment for agents to live in. This virtual environment (1) offers a medium that agents can use to exchange information and coordinate their behavior, and (2) serves as a suitable abstraction to shield low-level physical processing from the AGV agents. Since the only infrastructure available to the AGVs is a wireless network, the virtual environment is necessarily distributed over the AGVs. Synchronization of the state of the virtual environment is provided by ObjectPlaces, a middleware infrastructure that offers support to exchange and share information among nodes in mobile and ad-hoc networks. In this paper, we demonstrate how the environment is used creatively in the design of a MAS solution, helping to manage the complexity of engineering a complex real-world application. 1

How and why the presence of a person directly affects the perception and action of another person is a phenomenon that has been approached in a limited and piecemeal fashion within psychology. This kind of diffuse strategy has failed to capture the jointness of perception and action within and between people. In contradistinction, the authors offer a perspective that retains both integrally social features (e.g., involves interaction) and yet adequately exploits the current state of knowledge regarding the ecological properties of perception–action, while at the same time drawing on aspects of dynamic systems theory. In this article the authors review the best attempts to examine how one individual affects another’s perceptions and actions in the emergence of a social unit of action. Two important approaches, the individual-level and cognitive dynamics approaches, have yielded insights that derive in significant degree from principles of ecological psychology and/or dynamical systems theory. Prototypic of the individual-level approach is a focus on what can be perceived by coactors with the aim of uncovering how the dispositional qualities (affordances) of another person are informationally specified during social interaction. In contrast, the cognitive dynamics approach simulates dynamical characteristics of cognition and psychological influence with the aim of uncovering how cooperative interaction emerges out of its component parts. The authors argue that these approaches involve, respectively, insufficient mutuality and insufficient embodiment. Consequently, a social synergy perspective is discussed that approaches the problem of socially cooperative interaction at the relational, nonreductive level, using novel methods to examine how social perception and action emerge through self-organizing processes.

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Abstract. Research on situated multi-agent systems investigates how to model a distributed application as a set of cooperating autonomous entities (agents) which are situated in an environment. Many fundamental issues remain unrevealed in this research area. A profound understanding of these issues, however, is necessary before situated multi-agent systems can be applied to industry-strength applications. We use the abstract application called the Packet-World quite extensively as a test bed for investigating, experimenting and evaluating fundamental concepts and mechanisms. Examples are active perception, decision making of situated agents, synchronization of simultaneous actions and indirect coordination. The Packet-World has direct connections with real-world applications, such as the decentralized control of a warehouse transportation system through unmanned vehicles. In this article, we describe the Packet-World and we give an overview of our research for which we have used the Packet-World as a test bed.