@InProceedings{AAAI19-Hanna,
  author = {Josiah P. Hanna and Guni Sharon and Stephen D. Boyles and Peter Stone},
  title = {Selecting Compliant Agents for Opt-in Micro-Tolling},
  booktitle = {Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19)},
  location = {Honolulu, Hawaii, USA},
  month = {January}, 
  year = {2019},
    abstract = {
     This paper examines the impact of tolls on social welfare in the context of a transportation network in which only a portion of the agents are subject to tolls. More specifically, this paper addresses the question: which subset of agents provides the most system benefit if they are compliant with an approximate marginal cost tolling scheme? Since previous work suggests this problem is NP-hard, we examine a heuristic approach. Our experimental results on three real-world traffic scenarios suggest that evaluating the marginal impact of a given agent serves as a particularly strong heuristic for selecting an agent to be compliant. Results from using this heuristic for selecting 7.6\% of the agents to be compliant achieved an increase of up to 10.9\% in social welfare over not tolling at all. The presented heuristic approach and conclusions can help practitioners target specific agents to participate in an opt-in tolling scheme.},

  bib2html_pubtype = {Refereed Conference},
  bib2html_rescat = {Autonomous Traffic Management, Game Theory, Multiagent Systems, },
  bib2html_funding = {NSF, Intel, Raytheon, Lockheed Martin, IBM}
}