Generalizing and Executing Plans
نویسنده
چکیده
We address the problem of generalizing a plan to maximize the flexibility and robustness with which an agent can execute it. A key area of automated planning is the study of how to generate a plan for an agent to execute. The plan itself may take on many forms: a sequence of actions, a partial ordering over a set of actions, or a procedure-like description of what the agent should do. Many forms can be viewed as a family of plans. The question remains as to how the agent should execute the plan. For simple forms of representation (e.g., a sequence of actions), the answer to this question is straightforward. However, when the representation is more expressive (e.g., a GOLOG program or HTN (Levesque et al. 1997; Erol, Hendler, and Nau 1995)), or the agent is acting in an uncertain world, execution can be considerably more challenging. We focus on generalizing different plan representations before execution begins into a form that allows for nimble and robust execution by an agent.
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