Architectures That Plan and Predict

Planning is arguably one of the most important capabilities for an intelligent agent to possess. In almost all cases, the tasks which these agents must carry out are expressed as goals to be achieved; the agent must then concoct a series of actions designed to achieve this goal.

The ability to plan is closely linked to the agent's representation of the world. It seems that effective planning requires that 1) knowledge of the world is available to the planner, and since most worlds in which we are interested are reasonably complex, this is a strong motivation for implementing 2) a symbolic representation of knowledge. Typically, this knowledge contains information about possible actions in the world, which is then used by the planner in constructing a sequence of actions.

Planning itself is a prerequisite for several other capabilities that are often instantiated in intelligent agents. Certainly, problem solving relies heavily on planning, as most approaches to problem solving consist of incremental movements toward a solution; planning is integral to assembling these steps. Learning and planning have a reciprocating relationship wherein planning creates a new method for carrying out a task, which can then be learned for future use by the planner.

The following list of intelligent agents represents a variety of approaches to solving the problems associated with implementing the planning capability.


Click here to see a discussion on the dichotomy between planning and reactivity.
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