Lesson Traverso, Paolo (2004), Automated Planning: Theory







Lesson # Case Studies

Kirtan A. Patel

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International American University

BUS 530: Management Information Systems

Muhammad Ashfaque

January 26, 2018

 Automated Planning and Scheduling

Automated planning and scheduling, which is also known as AI Planning. This is a section of self-thinking technology that worries the existence of procedures, usually achieved by unmanned vehicles, and self-governing robots. It’s not like conventional control and organization issues, but this designs are intricate and need to be attained and enhanced.

The planning can be done offline in the familiar environment with available models. Prior to execution, the clarifications can be collected and evaluated. The planning strategy often needs to be revised online in the dynamically unfamiliar environment. The policies and models must be modified. In Artificial intelligence, the solutions usually made of iterative trial and errorful. These include verity of things like dynamic programming, reinforcement learning, and combinatorial optimization. Action Language is the word usually used in the planning and scheduling description.

Review/Analysis of the Case

Analysis of Findings

The planning problem is being used to manufacture a bonded state which contains a goal state. Many different factors are applied while planning. Some planning problems are classified depending on the problems properties.

The easiest planning problem also known as classical problems is defined by:

·         a unique known initial state,

·         duration less actions,

·         deterministic actions,

·         which can be taken only one at a time,

·         And a single agent.


Summary and Conclusions

The AI Planning implementation is far more advanced and requires a lot of research and practice to implement in a way that it will work without any problems. Since the complications are too high, there are many ways to solve the problems faced implementing planning in practice.

Like all other technologies, AI planning can also be achieved by lots of trial and error implementations and by the right planning solutions.



Ghallab, Malik; Nau, Dana S.; Traverso, Paolo (2004), Automated Planning: Theory and Practice, Morgan Kaufmann, ISBN 1-55860-856-7

Vlahavas, I. “Planning and Scheduling”. EETN. Archived from the original on 2013-12-22.