CODEWITHSUNDEEP
algorithmartificial-intelligenceplanning
fiscsp
fiscsp

Reputation: 37

Fast Downward planner

I am currently studying the AI fast downward planner, and I would like some help in this area. I know that the planner receives a domain.pddl file and a problem.pddl file, in addition, it receives a search algorithm and a heuristic function.

Many planners (not just the fast downward - ex. the pyperplan planner) gives us the opportunity to modify or create our new search algorithms to reach a solution. But as I have seen there are so many search algorithms already. My question is: what is the idea in implementing our own search algorithm? or am

Am I missing something?

Upvotes: 0

Views: 1052

Answers (1)

Flogo
Flogo

Reputation: 1868

I'm not sure what your question is, so I'm going to give two different answers.

Why do planning systems like Fast Downward have the option to write your own search algorithms, heuristics, etc.?

Automated domain-independent planning is an active research area where new ideas are constantly developed (for example at ICAPS). Implementing a new idea to evaluate is is much easier if you can base the implementation on an existing framework than if you have to start from scratch every time. It also helps with comparability. For example, if you develop a new search algorithm but leave the heuristic the same, your implementation is much easier to compare to a baseline if the baseline uses the same heuristic implementation. That is why a lot of work is based on Fast Downward an similar frameworks.

How do I come up with an idea for a new search algorithm?

This is much harder to answer. As a general approach I would say: Try to find cases where existing search algorithms "don't get it", for example, a problem that you can solve by looking at it but the search algorithm fails to solve it. Then try to figure out what you did to solve it, generalize that idea so it works on other cases as well and write it down as an algorithm.

Upvotes: 2

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