Information domain modeling of emergent phenomena

Study in fields such as distributed artificial intelligence (DAI), decentralized artificial intelligence (DzAI), parallel artificial intelligence (PAI), multiagent systems (MAS), computer supported cooperative work (CSCW), artificial life (AL), and complex adaptive systems (CAS) is concerned with the cooperation, coordination, communication, and coherence of multiple agents working together to achieve a common goal. The notion that the ability of a collective can exceed the sum of the individuals is a fundamental concept and a generally accepted truth. However, no general theoretical explanation exists as to why this could or should be the case. This dissertation explores such an explanation by considering a property called emergent capacity—a measure of collective behavior arising from the complex interactions among individual components. A theoretical space, called the information domain, is formulated allowing modeling, analysis, and calculation of emergent capacity. An equation for emergent capacity is presented and is validated by explaining and predicting empirical results in the fields of AL and CAS.