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Stephen Flockton.  What is my Project?  What is Planning?  Advantages and Disadvantages of Planning.  Description of the Product.  Product Demonstration.

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Presentation on theme: "Stephen Flockton.  What is my Project?  What is Planning?  Advantages and Disadvantages of Planning.  Description of the Product.  Product Demonstration."— Presentation transcript:

1 Stephen Flockton

2  What is my Project?  What is Planning?  Advantages and Disadvantages of Planning.  Description of the Product.  Product Demonstration.  Problems/Successes.  Conclusions from the Project.

3 This project is about:  Investigating the application of planners in video games and academia.  Discovering the strengths and weaknesses of planners.  Evaluating planners as an AI technique  Creating and testing a planner to gain a better insight to their application.

4 F.E.A.R – First Encounter Assault Recon Monolith Productions 2005 Stalker: Shadow of Chernobyl GSC Game World

5 Planning is an AI technique where agents create plans solve their own personal goals. A plan consists of a list of actions which lead to the agents goal being solved. Goal – Kill Target. Example Plan: Find GunReload GunFire at Target

6 A planning system consists of the following:  A World State Definition  Actions  Goals  Planning Engine

7 Goal Satisfied Check World State Create Goal Form Plan Perform Action Update World State Plan Invalidated

8  Flexibility  Modularity  Believability  Emergent Behaviour  Ease of Debugging

9  Additional work on initial architecture  Heavy need for optimisation  Not right for every game  Hard to get the frequency of plans just right

10 This product is a custom built planner which solves a simple domain model in real time. The planner is based on a Iteratively deepening depth first search of world states. The domain is a simple scenario originally created by Lee McCluskey.

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12 The planner is in time where M is the mean number of actions, K is the search depth and N is the number of actions to the goal.

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14 A custom symbolic World State was created for the planner. It is based on Jeff Orkin's Implementation in FEAR Consists of several enumerated types which make up an object. All objects can then be represented symbolically

15  Initial difficulties with the input language.  Problems with depth first search.  Keeping the execution speed down.  Initial design of World State definition was a challenge to design.  Long plans take exponential time

16  World State definition very flexible and expressive.  Planner can make intelligent plans  Planner can make short plans very fast  Improvement of personal design skills

17 AI planning is key to the next set of advances in video game technology. Flexibility and modularity make it ideal for the game development process. I’ve personally learned a lot from this project.

18  Team based AI planning.  Investigation into wider system integration.  Research into speed increases and heuristics

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