Memory-based mechanisms for economic agents

Gil Dollberg, Aviv Zohar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We investigate the relation between money and memory in computational systems. To do so, we introduce a model in which agents have a state associated with them that is known to those interacting with them. The joint states of agents who interact successfully change according to some prescribed probability distribution. We show that such mechanisms can in fact encode and generalize a rich variety of monetary mechanisms, while requiring very little memory per agent to represent state, possibly even a single bit. We explore how monetary considerations like the total amount of money apply in our model, and seek memory-based mechanisms that increase social welfare. We examine the natural encoding of a token-based system in memory, in which tokens are exchanged and conserved during each transaction. We find that mechanisms that use price discrimination or do not conserve tokens can provide higher social welfare.

Original languageAmerican English
Title of host publication16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
EditorsEdmund Durfee, Michael Winikoff, Kate Larson, Sanmay Das
Pages1523-1525
Number of pages3
ISBN (Electronic)9781510855076
StatePublished - 2017
Event16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 - Sao Paulo, Brazil
Duration: 8 May 201712 May 2017

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume3

Conference

Conference16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
Country/TerritoryBrazil
CitySao Paulo
Period8/05/1712/05/17

Keywords

  • Economic mechanisms
  • Memory
  • Money

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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