Multi-agent multi-team systems are commonly seen in environments where hierarchical layers of goals are at play. For example, theater-wide combat scenarios where multiple levels of command and control are required for proper execution of goals from the general to the foot soldier. Similar structures can be seen in game environments, where agents work together as teams to compete with other teams. The different agents within the same team must, while maintaining their own ‘personality’, work together and coordinate with each other to achieve a common team goal. This research develops strategy-based multi-agent multi-team systems, where strategy is framed as an instrument at the team level to coordinate the multiple agents of a team in a cohesive way. A formal specification of strategy and strategy-based multi-agent multi-team systems is provided. A framework is developed called SiMAMT (strategy- based multi-agent multi-team systems). The different components of the framework, including strategy simulation, strategy inference, strategy evaluation, and strategy selection are described. A graph-matching approximation algorithm is also developed to support effective and efficient strategy inference. Examples and experimental results are given throughout to illustrate the proposed framework, including each of its composite elements, and its overall efficacy. This research make several contributions to the field of multi-agent multi-team systems: a specification for strategy and strategy-based systems, and a framework for implementing them in real-world, interactive-time scenarios; a robust simulation space for such complex and intricate interaction; an approximation algorithm that allows for strategy inference within these systems in interactive-time; experimental results that verify the various sub-elements along with a full-scale integration experiment showing the efficacy of the proposed framework.

Thesis (M. of Military Art and Science)--U.S. Army Command and General Staff College, 2007. / The original document contains color images. Title from title page of PDF document (viewed on May 27, 2008). Includes bibliographic references.

The thesis is focused on the area of Business Intelligence Governance that seeks to management BI as a complex environment in an organization. The goal of this thesis is to create comprehensive BIG framework that will help to understand and lead BI, to support business strategy execution. The fist part of this thesis is introduction to the area of BIG. It contains definition of the term BI, description of trends in BI, definition of the term BIG and the answer on question Why do we need to governance BI. The second part focuses on description and evaluation of existing BIG instruments. The third part handles about new BIG framework and authorities. It describes particular building blocks of the framework and discovers structure of BIG authorities.