OVERVIEW Overview of Concepts & Ideas Introduction CONCEPTS Evolution & Selection Nonlinearity Self-Organization TERMS Adaptation Agent Complexity Emergence Feedback Fitness Landscapes Internal Models Multi-Agent Computer Models Nested Hierarchies Randomness & Chance RECOMMENDED READING				TERMS: AGENTS We might as well be up front about the term "agents:" it is "jargon" used in computer science and economics. Why might you care to know this piece of jargon? The main reason is that it is often a more convenient way to talk about different types of complex systems that share essential features. For example, if you sell chairs, sofas, beds, lamps, etc., you might find it more convenient to have a more general word to talk about what you sell: you sell furniture. When we talk about the components of complex systems, they might be atoms, molecules, cells, organs, animals, forests, businesses, economies, and galaxies. When we are trying to understand what processes or dimensions are common across such a vast range of phenomena, it is useful to have a generic term we can use to describe these different parts of these different complex systems. Researchers in computer science who develop computer models of complex systems have coined the term "agents." Essentially, agents are the individual active elements of a complex system that interact in various ways. Each agent has its own internal states, rules, or strategies that determine its behavior in the environment. Atoms interact with each other in certain ways. For example, helium has 2 electrons and thus has a complete outer electron shell that does not combine with other elements (i.e., it is inert), unlike hydrogen that only has a single electron and therefore will combine with other atoms that has an "extra" electron to share (H2O). In contrast, living agents interact based on internal models or rules. Simple organisms such as ants have a relative few simple rules that govern their behavior while a person or an organization will typically have a great number of potential models or rules that influence behavior. There is another interesting aspect about agents in complex systems: agents themselves often consist of complex systems which exist at different hierarchical levels. For example, the cells in your body may be regarded as "agents" while you (at a "higher" level of the hierarchy) are an agent that interacts with other agents in your environment, such as your friends, pets, trees, automobiles, and so on. Previous | Overview | Concepts | Terms | Next
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