[agents] Tutorial on Cooperative Decision Making in Sequential Multiagent Settings @ AAMAS-13

[Christopher Amato]

Cooperative Decision Making in Sequential Multiagent Settings
1 day tutorial
At AAMAS 2013
May 6 or 7th, 2013
http://www.st.ewi.tudelft.nl/~mtjspaan/tutorialDMMS/
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*** Note there also is a tutorial on *Self-Interested* Decision Making  in Sequential Multiagent Settings at AAMAS 2013, see the webpage above for  details ***


Summary
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Multiagent decision making is a core area of research within the agents community. Of late, this area has witnessed a tremendous growth in interest among the community. The tutorial will span the range of cooperative multiagent interactions of increasing generality, and study a set of optimal and approximate solution techniques to sequential decision making in these multiagent contexts. By providing an accessible and applications-driven overview of the literature in multiagent decision making, the tutorial will provide an impetus to those interested in researching or practicing in this promising area.


Description
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Choosing optimally among different lines of actions is a key aspect of autonomy in agents. The process by which an agent arrives at this choice is complex, particularly in environments shared with other agents. This tutorials will focus on how to make optimal and approximately optimal decisions in multiagent settings. The emphasis will be on decision making in sequential interactions, which are often encountered in networking, surveillance, exploration as well as search and rescue applications. The tutorial offers a one-day set of lectures introducing relevant background literature such as aspects of decision and game theory.  The material will be dedicated to cooperative decision making.


Structure of the Tutorial
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Part I is designed to provide the necessary background and basic techniques, and Part II discusses both in breadth and depth the major advancements of the multiagent decision making.

Part I: Frameworks for Multiagent Decision Making under Uncertainty Introduction
       - Motivating domains
       - Requirements for the multiagent decision model and solution
       - Overview of the basic framework and simple solution methods for them (MDP, POMDP, Bayesian Games)
       
Part II: Cooperative Models and Algorithms
       - Dec-POMDP solution concepts
       - General solution methods
       - Exploiting structured problems
       - Other topics (Communication, Learning)
       - Application problem domains and software tools


Target Audience
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The tutorial is aimed at graduate students and researchers who want to enter this emerging field or to better understand recent results in this area and their implications on the design of multi-agent systems. Participants should have a basic knowledge of probability theory, and preferably, utility theory.


Tutors (in alphabetical order)
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    Christopher Amato, MIT
    Prashant Doshi, University of Georgia
    Frans Oliehoek, Maastricht University
    Zinovi Rabinovich, Mobileye
    Matthijs Spaan, Delft University of Technology
    Stefan Witwicki, INESC-ID and Instituto Superior Técnico

This tutorial is a follow-up to ones at AAMAS 2012, 2011 and 2010.