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@InProceedings{AAAI19-Hanna,
  author = {Josiah Hanna and Guni Sharon and Stephen Boyles and Peter Stone},
  title = {Selecting Compliant Agents for Opt-in Micro-Tolling},
  booktitle = {Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI)},
  location = {Honolulu, HI},
  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.
  },
}