Andrew CourterTexas Tech University

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PKS• Why PKS?• STRIPS• The Databases• Inference Algorithm• Extended Features

PKS Examples Conclusion and Future Work Questions

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Planning with Knowledge and Sensing System

Goal: To come up with natural plans with an incomplete set of knowledge

Implement new features in PKS that will be able to solve a wider range of problems

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(Stanford Research Institute Problem Solver) is the framework that PKS is based on

The known world is represented in a database and actions are represented as updates to the database

PKS uses multiple databases and stores knowledge instead of the state of the world

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The first database is like a STRIPS database(containing ground literals) except that both positive and negative facts are allowed

The second database is used for plan time reasoning about sensing actions

The third database stores information about function values that will be known at execution time

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The fourth database contains disjunctive knowledge

If one ground literal is found to be true the rest of the literals become false or if all but one literals are false the remaining one is true

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Examines database contents to determine if an actions preconditions hold true

Also determines what the effects of an action should be activated and whether or not a plan achieved its goal

Four different rules are used to determine conclusions about the effects

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The PKS has a complete knowledge of action effects and non-effects

The agent’s actions are the only source of change in the world

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Knowing that a final conclusion relates to the initial state and all other states

Numeric expressions used in evaluating numbers(evaluated down to a number at plan time)

Finite valued functions in the exclusive-or knowledge database

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The PKS system was fine tuned and can handle a wider range of planning problems using the new inference algorithm

In the problems a know-whether state was achieved

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Develop extensions to handle unknown numeric quantities

Current system is unable to treat unknown file sizes in a general way in the Unix example

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On page 2, they discuss the Kv section how, can you guarantee the value will become known? Do you have an example? Why can’t they make the numeric evaluation work with numbers not known at run time? Can you explain the painted door problem, I am confused?

What happens if the algorithm cannot deduce a plan given the current inputs? Does it stop or does it try the plan that considered a "best fit"? What is STRIPS?

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Does the PKS guarantee optimal solutions (plans)?

When a human does not know exactly how something works or to do, they try something that they think of right on the spot, do you think this can ever be accomplished with these techniques?

Can you give us some examples to explain the application of PKS?

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