Adaptive Constraint-Based Agents in Artificial Environments

[INTRODUCTION]   [AI for Games]   [Agents]   [Planning]   [Search Paradigms]   [Search Frameworks]   [Conclusion]

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(Related publication: [PUBLink])

A crucial aspect of an agent is the way its behavior is determined, i.e., what has to be done when. If there is to be no restriction on reactive actions with predetermined behavior patterns, an underlying planning system is needed. A great deal of research has been done on planning, and a wide range of planning systems have been developed, e.g., STRIPS [PUBLink], UCPOP [PUBLink], PRODIGY [PUBLink], TLPlan [PUBLink] and SHOP [PUBLink]. Many recent approaches are based on Graphplan [PUBLink] and SATPLAN [PUBLink] [PUBLink].

The basic planning problem is given by an initial world description, a partial description of the goal world, and a set of actions/operators that map a partial world description to another partial world description. A solution is a sequence of actions leading from the initial world description to the goal world description and is called a plan. The problem can be enriched by including further aspects, like temporal or uncertainty issues, or by requiring the optimization of certain properties.


[INTRODUCTION]   [AI for Games]   [Agents]   [Planning]   [Search Paradigms]   [Search Frameworks]   [Conclusion]

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Last update:
May 19, 2001 by Alexander Nareyek