Some Issues in the Design of Market-Oriented Agents

In a computational market, distributed market agents interact with other agents primarily through the exchange of goods and services. Thanks to a well-developed underlying economic framework, we can draw on a rich source of analytic tools and theoretical techniques for designing individual agents and predicting aggregate behavior. For many narrowly scoped static problems, design of a computational market is relatively straightforward. We consider some issues that arise in attempting to design computational economies for broadly scoped, dynamic environments. These issues include how to specify the goods and services being exchanged, how these market-oriented agents should set their exchange policies, and how computational market mechanisms appropriate for idealized environments can be adapted to work in a larger class of non-ideal environments.

[1]  Jon Doyle,et al.  A Reasoning Economy for Planning and Replanning , 1994 .

[2]  Michael P. Wellman.  A Market-Oriented Programming Environment and its Application to Distributed Multicommodity Flow Problems , 1993, J. Artif. Intell. Res..

[3]  Michael P. Wellman.  Rationality in Decision Machines , 1995 .

[4]  Tad Hogg,et al.  Spawn: A Distributed Computational Economy , 1992, IEEE Trans. Software Eng..

[5]  S. Clearwater.  Market-based control: a paradigm for distributed resource allocation , 1996 .

[6]  Piotr J. Gmytrasiewicz,et al.  On Reasoning About Other Agents , 1995, ATAL.

[7]  Tad Hogg,et al.  Distributed Computation as an Economic System , 1995 .

[8]  S. Stich.  Dennett on Intentional Systems , 1981 .

[9]  Allen Newell,et al.  The Knowledge Level , 1989, Artif. Intell..

[10]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[11]  Michael P. Wellman,et al.  Market-oriented programming: some early lessons , 1996 .

[12]  J. Shoven,et al.  Applying general equilibrium , 1993 .

[13]  Eduardo Alonso Fernández,et al.  Rules of encounter: designing conventions for automated negotiation among computers , 1995 .

[14]  Michael Stonebraker,et al.  An economic paradigm for query processing and data migration in Mariposa , 1994, Proceedings of 3rd International Conference on Parallel and Distributed Information Systems.

[15]  Edmund H. Durfee,et al.  Recursive Agent Modeling Using Limited Rationality , 1995, ICMAS.

[16]  Tuomas Sandholm,et al.  An Implementation of the Contract Net Protocol Based on Marginal Cost Calculations , 1993, AAAI.

[17]  David R. Cheriton,et al.  A market approach to operating system memory allocation , 1996 .

[18]  Michael P. Wellman.  A computational market model for distributed configuration design , 1994, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[19]  Edmund H. Durfee,et al.  The Distributed Agent Architecture of the University of Michigan Digital Library , 1995 .

[20]  Randall Davis,et al.  Negotiation as a Metaphor for Distributed Problem Solving , 1988, Artificial Intelligence.

[21]  Yoav Shoham,et al.  Agent-Oriented Programming , 1992, Artif. Intell..

[22]  Nathaniel Rockwood Bogan,et al.  Economic allocation of computation time with computation markets , 1994 .

[23]  Rahul Simha,et al.  A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems , 1989, IEEE Trans. Computers.

[24]  Michael P. Wellman,et al.  A Simple Computational Market for Network Information Services , 1995, ICMAS.

[25]  Scott H. Clearwater,et al.  Saving energy using market-based control , 1996 .

[26]  Donald F. Ferguson,et al.  Economic models for allocating resources in computer systems , 1996 .