Teamwork is a critical capability in multi-agent environments. Many such environments mandate that the agents and agent-teams must be persistent i.e., exist over long periods of time. Agents in such persistent teams are bound together by their long-term common interests and goals. This paper focuses on flexible teamwork in such persistent teams. Unfortunately, while previous work has investigated flexible teamwork, persistent teams remain unexplored. For flexible tamwork, one promising approach that has emerged is model-based, i.e., providing agents with general models of teamwork that explicitly specify their commitments in teamwork. Such models enable agents to autonomously reason about coordination. Unfortunately, for persistent teams, such models may lead to coordination and communication actions that while locally optimal, are highly problematic for the team's long-term goals. We present a decisiontheoretic technique to enable persistent teams to overcome such limitations of the m...

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Abstract. In order to simulate the coordination of non-governmental organizations (NGOs) in humanitarian relief, we propose a theoretical framework for the emergence of collaborative projects and corresponding coalitions. In this framework, NGOs are represented as autonomous and heterogeneous agents who are embedded in social networks. They interact with each other in various ways, deliberatively identify collaborative projects they would like to work on, and form coalitions for collaborative projects. The impacts of several social network factors are also incorporated into the coordination framework. 1

Foundation, or the U.S. government. The study of complex social and technological systems, such as organizations, requires a sophisticated approach that accounts for the underlying psychological and sociological principles, communication patterns and the technologies within these systems. Social Network Analysis and link analysis have since inception operated on the cutting edge bringing together mathematical analysis of social structures and qualitative reasoning and interpretation. As available computing power grew, social network-based models have become not only an analysis tool, but also a methodology for building new theories of social behaviour and organizational evolution, frequently through the creation of simulation models. This work examines the past approaches of creating Social Network-based semantically consistent and interpretable models of social structure and social

simulation, model validation, organization theory, network organization, organizational Network organizations offer learning, adaptive and resilient capabilities that are particularly useful in high velocity environments as these capabilities allow the organization to effectively respond to change. The dynamic, evolutionary nature of network organizations affords such advantageous capabilities. Although the advantages of network organizations are well-studied, the risks associated with them are not. Of interest is the study of critical personnel. Understanding criticality within an organization can help improve performance and protect against the risk of loss. But the study of critical personnel has traditionally used static structural representations that do not represent the dynamic nature of network organizations. This thesis advances the study of critical personnel risks in network organizations

A century of research on small groups has yielded bountiful findings about many specific features and processes in groups. Much of that work, in line with a positivist epistemology that emphasizes control and precision and favors the laboratory experiment over other data collection strategies, has also tended to treat groups as though they were simple, isolated, static entities. Recent research trends that treat groups as complex, adaptive, dynamic systems open up new approaches to studying groups. In line with those trends, a theory of groups as complex systems is offered and some methodological and conceptual issues raised by this theory are identified. A 3-pronged research strategy based on theory development, computational modeling, and empirical research that holds promise for illuminating the dynamic processes underlying the emergence of complexity and the ongoing balance of continuity and change in groups is proposed. As the 20th century ends and the 21st begins, we look back on a century of research on groups, take stock of where the accumulated work of the century

Despite a large number of studies, the effect of organizational structure on the performance and the individual cognition of its members is still not well understood. Our research aims at developing tools and formalisms to model organizations and evaluate their performance under different circumstances. Organizational effectiveness depends on many factors, including excellence, effective planning and capability to understand and match context requirements. Different organizational structures are clearly better matched to certain problems and context requirements than others, but methods to determine which structure better fits the requirements and goals of a group are non-existent. We propose a combination of agent-based formal models and agent-base simulation that supports the analysis of the congruence of different organizational structures to different problems and requirements. 1.

: Within the resource-based view of the firm, a dynamic story has emerged in which the knowledge accumulated over the history of a firm and embedded in organizational routines and structures influences the firm's ability to recognize the value of new resources and capabilities. This paper explores the possibility of firms to select organizational designs that increase the likelihood that they will recognize and value rent-producing resources and capabilities. A computational model is developed to study the tension between an organization's desire to explore its environment for new capabilities and the organization's need to exploit existing capabilities. Draft. Please do not cite without permission. Comments welcome. I would like to thank John Miller, Scott Page, Mike Ryall, Tomas Klos, Bill Watkins, Peter Wurman, Rob Bernard and the rest of the participants at the 1997 Santa Fe Institute Workshop on Computational Economics for their insightful comments. ã 1998 Michael J. Lenox 2 ...