Edited by Matthias Ruth and Brynhildur Davidsdottir
Chapter 6: Agent-Based Analysis of Dynamic Industrial Ecosystems: An Introduction
6. Agent-based analysis of dynamic industrial ecosystems: an introduction Marco A. Janssen INTRODUCTION The agent-based approach, which is used in the chapters of this part, explicitly studies the emergent macro-level phenomena from interactions at the microlevel between autonomous agents. Individual attributes and strategies of the agents can inﬂuence the emergent patterns, the information derived by the agents, and the structure of the network of agents. Agent-based analysis can be performed by conceptual (Chapter 9) as well as computational approaches (Chapters 7 and 8). The computational approach is referred to as agent-based modeling. Agent-based modeling within social science has its roots in the early 1970s. Initially developed during the 1940s, the technical methodology of computational models of multiple interacting agents arose when John von Neumann started to work on cellular automata (von Neumann 1966). A cellular automata is a set of cells where each cell can be in one of multiple predeﬁned states, such as forest land or farm land. Changes in the state of a cell occur based on the prior states of the cell’s own history and the history of neighboring cells. Cellular automata became more popular in light of a creative application by John Conway, named the Game of Life (Gardner 1970). The Game of Life illustrated how the following simple rules of local interaction could lead to the emergence of complex global patterns. In contrast to cellular automata, agent-based models enable a researcher to examine the heterogeneity of agents beyond their speciﬁc location and...
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