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  Planning for Concurrent Durative Uncertain Actions
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Project faculty
 Dan Weld
Project students

Planning for Concurrent Durative Uncertain Actions


Probabilistic planning problems are often modeled as Markov decision processes (MDPs), which assume that a single action is executed per decision epoch and that actions take unit time. However, in the real world it is common to execute several actions in parallel, and the durations of these actions may differ. We develop extensions to MDPs that incorporate these features. In particular, we propose the model of Concurrent MDPs, which allows simultaneous execution of multiple unit-duration actions at a time point. We extend this to handle concurrent durative actions with deterministic as well as stochastic durations.

We release the code for our COMDP solver described in the AAAI'04 paper. Please download it here.


  1. Mausam, Daniel S. Weld, Solving Concurrent Markov Decision Processes, AAAI 2004, San Jose, CA July 2004, Extended Technical Report.
  2. Mausam, Daniel S. Weld, Concurrent Probabilistic Temporal Planning, ICAPS 2005, Monterey, CA June 2005, An earlier version, in AAAI 2004 Workshop on Learning and Planning in Markov Processes - Advances and Challenges, San Jose, CA July 2004.
  3. Mausam, Daniel S. Weld, Challenges for Temporal Planning with Uncertain Durations, ICAPS 2006, The English Lake District, UK June 2006.
  4. Mausam, Daniel S. Weld, Probabilistic Temporal Planning with Uncertain Durations, AAAI 2006, Boston, MA July 2006.
  5. Mausam, Daniel S. Weld, Planning with Durative Actions in Stochastic Domains, JAIR 31:33-82, Jaunuary 2008..

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