On the benefits of cheating by self-interested agents in vehicular networks

Raz Lin*, Sarit Kraus, Yuval Shavitt

*Corresponding author for this work

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

Abstract

As more and more cars are equipped with GPS and Wi Fi transmitters, it becomes easier to design systems that will allow cars to interact autonomously with each other, e.g., regarding traffic on the roads. Indeed, car manufacturers are already equipping their cars with such devices. Though, currently these systems are a proprietary, we envision a natural evolution where agent applications will be developed for vehicular systems, e.g., to improve car routing in dense urban areas. Nonetheless, this new technology and agent applications may lead to the emergence of self-interested car owners, who will care more about their own welfare than the social welfare of their peers. These car owners will try to manipulate their agents such that they transmit false data to their peers. Using a simulation environment, which models a real transportation network in a large city, we demonstrate the benefits achieved by self-interested agents if no counter-measures are implemented.

Original languageEnglish
Title of host publicationAAMAS'07 - Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems
Pages327-334
Number of pages8
DOIs
StatePublished - 2007
Event6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS'07 - Honolulu, HI, United States
Duration: 14 May 200818 May 2008

Publication series

NameProceedings of the International Conference on Autonomous Agents

Conference

Conference6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS'07
Country/TerritoryUnited States
CityHonolulu, HI
Period14/05/0818/05/08

Keywords

  • Agent-based deployed applications
  • Artificial social systems

Fingerprint

Dive into the research topics of 'On the benefits of cheating by self-interested agents in vehicular networks'. Together they form a unique fingerprint.

Cite this