Sequential Decision Making for Intelligent Agents: Papers from the AAAI Fall Symposium

Matthijs T. J. Spaan (Editor), Frans A. Oliehoek (Editor), Pascal Poupart (Editor)

Research output: Book/ReportBookScientificpeer-review


Sequential decision making under uncertainty has gained significant traction in Artificial Intelligence. In many applications, dealing explicitly with uncertainty regarding the effects of actions, state of the environment and possibly the behavior of other agents is crucial to achieve satisfactory task performance. Decision-theoretic planning models like the Markov decision process (MDP), the partially observable MDP (POMDP) and their many multiagent extensions have emerged as the dominant paradigm for this purpose. This symposium provided a dedicated forum for researchers of computational sequential decision making under uncertainty to meet and share ideas.
Original languageEnglish
PublisherAssociation for the Advancement of Artificial Intelligence (AAAI)
Number of pages118
ISBN (Print) 978-1-57735-752-0
Publication statusPublished - 2015

Publication series

NameFall Symposium Series Technical Report
PublisherAAAI Press
No.Technical Report FS-15-06


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