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Goal Achievement in Partially Known, Partially Observable Domains Allen Chang and Eyal Amir
 

Summary: Goal Achievement in Partially Known, Partially Observable Domains
Allen Chang and Eyal Amir
Computer Science Department
University of Illinois at Urbana-Champaign
Urbana, IL 61801, USA
{achang6,eyal}@cs.uiuc.edu
Abstract
We present a decision making algorithm for agents that act in
partially observable domains which they do not know fully.
Making intelligent choices in such domains is very difficult
because actions' effects may not be known a priori (partially
known domain), and features may not always be visible (par-
tially observable domain). Nonetheless, we show that an effi-
cient solution is achievable in STRIPS domains by using tra-
ditional planning methods. This solution interleaves planning
and execution carefully. Computing each plan takes time that
is linear in the planning time for the fully observable, fully
known domain. The number of actions that it executes is
bounded by a polynomial in the length of the optimal plan
in the fully observable, fully known domain. Our theoretical

  

Source: Amir, Eyal - Department of Computer Science, University of Illinois at Urbana-Champaign

 

Collections: Computer Technologies and Information Sciences