References

1

Tucker Balch.
Learning roles: Behavioral diversity in robot teams.
In Sen [21].

2

David Carmel and Shaul Markovitch.
Opponent modeling in multi-agent systems.
In Gerhard Weiss and Sandip Sen, editors, Adaption And Learning In Multi-Agent Systems, volume 1042 of Lecture Notes in Artificial Intelligence. Springer-Verlag, 1996.

3

Caroline Claus and Craig Boutilier.
The dynamics of reinforcement learning in cooperative multiagent systems.
In Proceedings of the Fifteenth National Conference on Artificial Intelligence, pages 746-752, Madison, WI, 1998.

4

Dave Cliff.
Evolving parameter sets for adaptive trading agents in continuous double-auction markets.
In Agents-98 workshop on Artificial Societies and Computational Markets, pages 38-47, Minneapolis, MN, May 1998.

5

Edwin De Jong.
Non-random exploration bonuses for online reinforcement learning.
In Sen [21].

6

David Easley and John Ledyard.
Theories of price formation and exchange in double oral auctions.
In Friedman and Rust [9], chapter 3, pages 63-98.

7

Jerzy Filar and Koos Vrieze.
Competitive Markov Decision Process.
Springer-Verlag, 1997.

8

Daniel Friedman.
The double auction market institution: A survey.
In Friedman and Rust [9], chapter 1, pages 3-26.

9

Daniel Friedman and John Rust, editors.
The Double Auction Market.
Addison-Wesley, 1993.

10

Piotr J. Gmytrasiewicz and Edmund H. Durfee.
A rigorous, operational formalization of recursive modeling.
In Proceedings of the First International Conference on Multiagent Systems, pages 125-132. AAAI Press, 1995.

11

Dhananjay Gode and Shyam Sunder.
Lower bounds for efficiency of surplus extraction in double auctions.
In Friedman and Rust [9], chapter 7, pages 199-220.

12

Junling Hu and Michael P. Wellman.
Self-fulfilling bias in multiagent learning.
In Proceedings of the Second International Conference on Multiagent Systems, pages 118-125, Kyoto, Japan, December 1996. AAAI Press.

13

Junling Hu and Michael P. Wellman.
Multiagent reinforcement learning: Theoretical framework and an algorithm.
In Proceedings of the Fifteenth International Conference on Machine Learning, pages 242-250, Madison, WI, July 1998. AAAI Press.

14

Leslie Kaelbling, Michael L. Littman, and Andrew W. Moore.
Reinforcement learning: A survey.
Journal of Artificial Intelligence Research, 4:237-285, May 1996.

15

Michael L. Littman.
Markov games as a framework for multi-agent reinforcement learning.
In Proceedings of the Eleventh International Conference on Machine Learning, pages 157-163. New Brunswick, 1994.

16

R. Preston McAfee and John McMillan.
Auctions and bidding.
Journal of Economic Literature, 25:699-738, 1987.

17

Rajami Nadella and Sandip Sen.
Correlating internal parameters and external performance.
volume 1221 of Lecture Notes in Artificial Intelligence. Springer-Verlag, 1997.

18

Guillermo Owen.
Game Theory.
Academic Press, San Diego, the third edition, 1995.

19

John Rust, John Miller, and Richard Palmer.
Behavior of trading automata in a computerized double auction market.
In Friedman and Rust [9], chapter 6, pages 155-198.

20

Mark Satterthwaite and Steven Williams.
The bayesian theory of the k-double auction.
In Friedman and Rust [9], chapter 4, pages 99-124.

21

Sandip Sen, editor.
Collected papers from the AAAI-97 workshop on multiagent learning. AAAI Press, 1997.

22

Richard S. Sutton and Andrew G. Barto.
Reinforcement Learning: An Introduction.
MIT Press/Bradford Books, March 1998.

23

Frank Thusijsman.
Optimality and Equilibria in Stochastic Games.
Amsterdam, the Netherlands : Centrum voor Wiskunde en Informatica, 1992.

24

Hirofumi Uzawa.
On the stability of Edgeworth barter process.
International Economic Review, 3(2):218-232, May 1962.

25

Hal R. Varian.
Microeconomic Analysis.
W. W. Norton & Company, New York, third edition, 1992.

26

José M. Vidal and Edmund H. Durfee.
The impact of nested agent models in an information economy.
In Proceedings of the Second International Conference on Multiagent Systems, pages 377-384. AAAI Press, December 1996.

27

José M. Vidal and Edmund H. Durfee.
Agents learning about agents: A framework and analysis.
In Sen [21].

28

Michael P. Wellman.
A market-oriented programming environment and its application to distributed multicommodity flow problems.
Journal of Artificial Intelligence Research, 1:1-22, 1993.

29

Michael P. Wellman and Junling Hu.
Conjectural equilibrium in multiagent learning.
Machine Learning, 33:1-23, 1998.