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9 - Automated Planning

Published online by Cambridge University Press:  30 April 2024

Deepak Khemani
Affiliation:
IIT Madras, Chennai
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Summary

So far in this book we have not thought of plans as explicit representations. True, we have referred to the path from the start node in the state space to the goal node as a plan, but that has been represented as a sequence of states. When we looked at goal trees we could also think of the solution subtree as a plan. Likewise, the strategy found by the SSS* algorithm is also a plan. But even here the intent of the problem solving agent is captured in terms of what state or board position will the player move to.

In this chapter we see problem solving from the perspective of actions. We represent plans explicitly, and the agent goes about the task of synthesizing a plan. At the simplest level, a plan is a sequence of named actions designed to achieve a goal. We begin with planning in the state space and move on to searching in the plan space. We also look at a two stage approach to planning with the algorithms Graphplan and Satplan.

We end with a brief look at some directions in planning in richer domains.

An intelligent agent acts in the world to achieve its goals. Given the state of the world it is in, and given the goals it has, it has to choose an appropriate set of actions. The process of selecting those actions is called planning. Planning is the reasoning side of acting (Ghallab, Nau, and Traverso, 2004). Planning and acting do not happen in isolation. A third process is an integral part of intelligent agency – perceiving. An agent senses the world it is operating in, deliberates upon its goals to produce a plan, and executes the actions in the plan. This is often referred to as the sense–deliberate–act cycle. The entire process may need to be monitored by the agent. Since the world may be changing owing to other agencies, it may even have to modify its plans on the fly.

There has been considerable work on autonomous agents that plan their activity. This became necessary in space applications where communication with Earth takes too long, necessitating autonomy. This was the case with the Mars rovers experiments by NASA, and even ten years after landing on Mars the rover Curiosity is still active.

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Publisher: Cambridge University Press
Print publication year: 2024

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  • Automated Planning
  • Deepak Khemani, IIT Madras, Chennai
  • Book: Search Methods in Artificial Intelligence
  • Online publication: 30 April 2024
  • Chapter DOI: https://doi.org/10.1017/9781009284325.010
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  • Automated Planning
  • Deepak Khemani, IIT Madras, Chennai
  • Book: Search Methods in Artificial Intelligence
  • Online publication: 30 April 2024
  • Chapter DOI: https://doi.org/10.1017/9781009284325.010
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Automated Planning
  • Deepak Khemani, IIT Madras, Chennai
  • Book: Search Methods in Artificial Intelligence
  • Online publication: 30 April 2024
  • Chapter DOI: https://doi.org/10.1017/9781009284325.010
Available formats
×