Cooperative Decision Making in Sequential Multiagent Settings

Self-Interested Decision Making in Sequential Multiagent Settings

Tutorials at AAMAS 2013, May 6 or 7, 2013

These tutorials run in parallel, you can only follow 1, and note that registration is separate.

Tutors (in alphabetical order):

These tutorials are a follow-up to ones at AAMAS 2012, 2011 and 2010.

Summary

These tutorials will span the range of multiagent interactions of increasing generality, and study a set of optimal and approximate solution techniques to sequential decision making in these multiagent contexts. Recognising the large volume of works, these tutorials are organised in two independent parallel streams: a) the cooperative decision making stream; and b) the adversarial decision making stream. Each stream is self-contained and will begin with the introduction of basic concepts and notions of decision and game theories, and then culminating with several advanced decision-theoretic models of complex agent interactions.

Acronyms covered: MDP, POMDP, Dec-POMDP, I-POMDP, POSG, ND-POMDP, TI-Dec-MDP, OC-Dec-MDP, TD-POMDP.

Description

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. These tutorials will focus on how to make optimal and approximately optimal decisions in multiagent settings. The will utilise the well-studied domain of search and human support applications to motivate and provide context for a range of multiagent interactions of increasing generality. The focus of this tutorial will be on decision making in sequential interactions, which are often encountered in the search and rescue applications. The tutorial offers two one-day independent streams of lectures with each stream being self-contained, introducing relevant background literature such as aspects of game theory. Stream-I will be dedicated to the cooperative decision making, while Stream-II will address the adversarial issues.

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.

Outline

STREAM I: Cooperative Multiagent Decision Making

  • Part I: Frameworks for Multiagent Decision Making under Uncertainty Introduction
    • Search and Rescue Applications in Disaster Management
    • 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

STREAM II: Self-Interested Multiagent Decision Making

  • Part I: Frameworks for Multiagent Decision Making under Uncertainty Introduction
    • Search and Rescue Applications in Disaster Management
    • 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: Self-interested models of decision making
    • Dynamic algorithms that support equilibrium
      • Repeated strategic games of complete information
      • Repeated Bayesian games
      • Partially Observable Stochastic Games
    • Modelling and utilising beliefs of others
      • Interactive POMDPs (I-POMDPs): framework, exact and approximate solution methods, software environments
    • Emerging applications of multiagent decision making
      • TTD-MDPs and multiagent Markov tracking

Material

This workshop is supported, in part, by the Portuguese Fundação para a Ciéncia e Tecnologia (FCT) and by Carnegie Mellon Portugal Program and its Information and Communications Technologies Institute, under project CMU-PT/SIA/0023/2009 ("MAIS-S"), and by the FCT (INESC-ID multiannual funding) under project PEst-OE/EEI/LA0021/2011.