Adaptive Constraint-Based Agents in Artificial Environments

[RESOURCES]   [The Orc Quest Example]   [The Nearby Wizard]   [Decision-Theoretic Planning]

[ Please note: The project has been discontinued as of May 31, 2005 and is superseded by the projects of the ii Labs. There won't be further updates to these pages. ]

The Orc Quest Example

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Imagine you are a computer-guided Orc in a computer game. Your interests are somewhat different from those of your philistine Orc friends. To get them a little more acquainted with the fine arts, you decided to surprise them with a ballet performance. As a highlight, five of those delicate humans are to play supporting roles. However, the uncivilized humans do not appreciate the charm of Orc-produced art and are extremely reluctant to participate. This makes it rather painful to catch a human and force him to take part in the performance, and much more painful to catch a whole group of them. On the other hand, going for a group saves time. This can be formalized as follows:

STATEVARS: Duration, Pain, Performers

INIT: Duration = 0, Pain = 0, Performers = 0
GOAL: Performers >= 5

ACTION catch_only_one:
  Duration += 2, Pain += 1, Performers += 1

ACTION catch_a_group:
  Duration += 5, Pain += 4, Performers += 3


[RESOURCES]   [The Orc Quest Example]   [The Nearby Wizard]   [Decision-Theoretic Planning]

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Last update:
May 19, 2001 by Alexander Nareyek