By a hierarchic system, or hierarchy, I mean a system that is composed of interrelated subsystems, each of the latter being in turn hierarchic in structure until we reach some lowest level of elementary subsystem. In most systems of nature it is somewhat arbitrary as to where we leave off the partitioning and what subsystems we take as elementary. Physics makes much use of the concept of “elementary particle,” although the particles have a disconcerting tendency not to remain elementary very long …
Empirically a large proportion of the complex systems we observe in nature exhibit hierarchic structure. On theoretical grounds we would expect complex systems to be hierarchies in a world in which complexity had to evolve from simplicity.
– Herbert A. Simon [1996]This chapter shows how an intelligent agent can perceive, reason, and act over time in an environment. In particular, it considers the internal structure of an agent. As Simon points out in the quote above, hierarchical decomposition is an important part of the design of complex systems such as intelligent agents. This chapter presents ways to design agents in terms of hierarchical decompositions and ways that agents can be built, taking into account the knowledge that an agent needs to act intelligently.
Agents
An agent is something that acts in an environment. An agent can, for example, be a person, a robot, a dog, a worm, a lamp, a computer program that buys and sells, or a corporation.
Agents interact with the environment with a body. An embodied agent has a physical body. A robot is an artificial purposive (page 13) embodied agent. Sometimes agents that act only in an information space are called robots or bots, but we just refer to those as agents.
Agents receive information through their sensors. An agent's actions depend on the information it receives from its sensors. These sensors may, or may not, reflect what is true in the world. Sensors can be noisy, unreliable, or broken, and even when sensors are reliable there still may be ambiguity about the world given the sensor readings. An agent must act on the information it has available. Often this information is very weak, for example, “sensor s appears to be producing value v.”
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