Metareasoning: Thinking about thinking

http://www.sis.uncc.edu/~anraja/Metareasoning

July 13-14, 2008, Colocated with AAAI 2008, Chicago, Illinois.

 

 

Call for Papers

Topics

Organizing Committee

Program Committee

Dates

Topics

Submission

Accepted Papers (new)

Workshop Program (new)

CFP in pdf

Manifesto

Figures Source

Photos

MetaReasoning Links

Call for Papers

The 21st century is experiencing a renewed interest in an old idea within artificial intelligence that goes to the heart of what it means to be both human and intelligent. This idea is that much can be gained by thinking of one's own thinking. Metareasoning is the process of reasoning about reasoning itself. As shown below, it is composed of both meta-level control of computational activities and the introspective monitoring of reasoning to evaluate and to explain computation. Meta-level control is the ability of an agent to efficiently trade off its resources between object level actions (computations) and ground level actions to maximize the quality of its decisions. Introspective monitoring is necessary to gather sufficient information with which to make effective meta-level control decisions or to explain failed object-level reasoning. This workshop will explore the implications of this model by examining the various aspects of metareasoning and models of self and their role in single-agent and multiagent applications.

The above figure and an accompanying manifesto are available on the web (www.mcox.org/Metareasoning/Manifesto). To increase coherence of the workshop sessions and to help attendees to relate heterogeneous positions, all authors are encouraged to include and reference at least one of a set of provided figures, either positively, negatively, or as a contrast to their own alternative models. The goal is to use this as a unifying theme. This is especially important because authors of selected papers will be invited to prepare chapters based on their workshop contributions for a forthcoming book on metareasoning. The workshop will not simply collect a loosely affiliated set of technical papers; rather, the objective is to present a cohesive story of what metareasoning is, what its limitations are, what benefits it promises, and how these promises can be implemented computationally.

This two day workshop will include a number of short paper presentations, thematically organized discussion sessions, a break-out problem-solving session with discussion, and two speakers. Professor Don Perlis from the University of Maryland, College Park, will present on day one and  Professor Aaron Sloman from the University of Birmingham, U.K. will present on day two. We also will include panel discussions after each group of paper presentations so that the audience can ask follow up questions that compare and contrast the related positions. Finally a special track will be targeted for the topic of evaluation of metareasoning systems.

 

Topics of Interest include:
  • Theoretical models of metareasoning
  • The integration of meta-level control and monitoring
  • Multiagent coordinated metareasoning
  • Meta-explanation and self-explanation
  • Self-adaptive systems and autonomic computing
  • Centralized versus distributed meta-level control
  • Human metacognition and metamemory
  • The role of state abstraction in metareasoning
  • Computational models of self and consciousness
  • Logical introspection and reflective logic programming
  • Bounded rationality
  • Learning agents and metareasoning
  • Evaluation of metareasoning systems
  • Theory of mind and social cognition
     

Organizing Committee:
Michael T. Cox (co-chair)                    Anita Raja (co-chair)
Senior Research Scientist                        Assistant Professor
Intelligent Computing                               Department of Software & Information Systems
BBN Technologies                                  University of North Carolina at Charlotte
Cambridge, MA 02138                           Charlotte, NC 28223
mcox@bbn.com                                       anraja@uncc.edu
(617) 873-3632                                      (704) 687-8651


Michael L. Anderson, Assistant Professor. Franklin & Marshall College.
David Leake, Professor, Indiana University.
Shlomo Zilberstein, Professor, University of Massachusetts.
 

Program Committee:
Vincent Conitzer, Assistant Professor, Duke University
Stefania Constanini, Professor, Univ. of L'Aquila, Italy
Ed Durfee, Professor, University of Michigan
Stan Franklin, Research Professor, University of Memphis
Andrew Gordon, Research Assistant Professor, University of Southern California
Eric Horvitz, Principal Researcher, Microsoft Research
Victor Lesser,  Professor, University of Massachusetts
Paul Robertson, Senior Research Scientist, BBN
Lenhart Schubert, Professor, University of Rochester
Steve Smith, Research Professor, Carnegie Mellon University

Important Dates:

Submission Deadline

 April 7, 2008

Acceptance Notification

 April 21, 2008

Camera-ready Copy

 May 5, 2008

AAAI-08 Workshop

 July 13-14, 2008

Submission Instructions:

We encourage the submission of high quality, original papers that are not submitted for publication elsewhere. The submission should not exceed eight pages in the AAAI style (www.aaai.org/Publications/Author/author.php), either in PostScript or PDF format. Surface mail address, e-mail addresses should be included for all contributing authors. Submissions must be emailed to either chair (mcox@bbn.com or anraja@uncc.edu) by the deadline period and must include and reference atleast one of the figures from http://ww.mcox.org/Metareasoning/Figs. Short position statements are also accepted.
 

Accepted Papers:

Long Papers:

  1. Josep Lluis Arcos, Oguz Mulayim and David Leake., Using Introspective Reasoning to Improve CBR System Performance

  2. Susan Epstein and Smiljana Petrovic. Learning Expertise with Bounded Rationality and Self-awareness

  3. Catriona Kennedy, Distributed Meta-Management for Self-Protection and Self-Explanation

  4. Brett Borghetti and Maria Gini, Weighted Prediction Divergence for Metareasoning

  5. Melinda Gervasio and Karen Myers, Question Asking to Inform Procedure Learning

  6. Tian Sang and Jiun-Hung Chen, Beyond Minimax: Nonzero-Sum Game Tree Search with Knowledge Oriented Players

  7. Shlomo Zilberstein, Metareasoning and Bounded Rationality

  8. Paul Robertson and Robert Laddaga, Meta-Reasoning for Multi-Spectral Satellite  Image Interpretation

  9. Fabrizio Morbini and Lenhart Schubert, Metareasoning as an Integral Part of Commonsense and Autocognitive Reasoning

  10. Jim Eilbert, Metacognition and the Process of Switching Between Reasoning Frames

  11. Boris Galitsky, Sergei Kuznetsov, and Boris Kovalerchuk, ,  Argumentation vs Meta-argumentation for the Assessment of Multi-agent Conflict

  12. Andrew Gordon, Jerry Hobbs and Michael Cox, Anthropomorphic Self-Models for Metareasoning Agents

  13. Jihie Kim and Yolanda Gil, Developing a Meta-Level Problem Solver for Integrated Learners

  14. Vincent Conitzer, Metareasoning as a Formal Computational Problem  

  15. Josh Jones and Ashok Goel, Retrospective Self-Adaptation of an Agentís Domain Knowledge:  Perceptually-Grounded Semantics for Structural Credit Assignment

  16. Stefania Costantini, Pierangelo Dell'Acqua, Luis Moniz Pereira, A Multi-layer Framework for Evolving and Learning Agents

  17. Anita Raja and Victor Lesser, Coordinating Agents' Meta-Level Control 

  18. Matt Schmill, Tim Oates, Mike Anderson,  Darsana Joysula, Don Perlis, Shomir Wilson, Scott Fults, The Role of MetaCognition in Robust AI Systems

  19. Aaron Sloman, Varieties of Meta-cognition in Natural and Artificial Systems

  20. Don Perlis, There's No "Me" in "Meta" - or Is There?

Short papers:

  1. Alexei Samsonovich, Kenneth Jong and Anastasia Kitsantas, Self-Awareness as Metacognition about Own Self Concept

  2. David Leake and Mark Wilson, Extending Introspective Learning from Self-Models

  3. Santiago Franco and Mike Barley, Research Statement: Predicted Best Admissible Heuristic Search  

  4. David Ostrowski and George Schleis, New Approaches for Meta-Heuristic Frameworks: A Position Paper

  5. Cindy Mason, Human-Level AI Requires Compassionate Intelligence and Affective Inference

  6. Michael Cox and Anita Raja,   Metareasoning: A Manifesto

 

 

Links: