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Published Articles >> Table of Contents >> Abstract
Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3 (AAMAS'04)
pp. 1197-1204
Fitting and Compilation of Multiagent Models through Piecewise Linear Functions
David V. Pynadath, University of Southern California
Stacy C. Marsella, University of Southern California
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AAMAS.2004.10219
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| Abstract |
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Decision-theoretic models have become increasingly
popular as a basis for solving agent and multiagent
problems, due to their ability to quantify the complex uncertainty
and preferences that pervade most nontrivial
domains. However, this quantitative nature also complicates
the problem of constructing models that accurately
represent an existing agent or multiagent system, leading
to the common question, "Where do the numbers
come from?" In this work, we present a method for exploiting
knowledge about the qualitative structure of a
problem domain to automatically derive the correct quantitative
values that would generate an observed pattern of
agent behavior. In particular, we propose the use of piecewise
linear functions to represent probability distributions
and utility functions with a structure that we can then exploit
to more efficiently compute value functions. More
importantly, we have designed algorithms that can (for example)
take a sequence of actions and automatically
generate a reward function that would generate that behavior
within our agent model. This algorithm allows us to
efficiently fit an agent or multiagent model to observed behavior.
We illustrate the application of this framework
with examples in multiagent modeling and social simulation,
using decision-theoretic models drawn from the alphabet
soup of existing research (e.g., MDPs, POMDPs,
Dec-POMDPs, Com-MTDPs).
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 Additional Information
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Citation:
David V. Pynadath, Stacy C. Marsella,
"Fitting and Compilation of Multiagent Models through Piecewise Linear Functions,"
aamas,
pp. 1197-1204,
Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3 (AAMAS'04),
2004
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