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Congestion Pricing and Learning in Traffic Network Games
Author(s) -
MELO EMERSON
Publication year - 2011
Publication title -
journal of public economic theory
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.809
H-Index - 32
eISSN - 1467-9779
pISSN - 1097-3923
DOI - 10.1111/j.1467-9779.2011.01503.x
Subject(s) - social planner , planner , externality , computer science , pigou effect , traffic network , convergence (economics) , mathematical economics , economics , road pricing , microeconomics , process (computing) , marginal cost , mathematical optimization , traffic congestion , mathematics , artificial intelligence , engineering , operating system , transport engineering , macroeconomics , economic growth
A stochastic model describing the learning process and adaptive behavior of finitely many users in a congested traffic network with parallel links is used to prove convergence almost surely toward an efficient equilibrium for a related game. To prove this result, we assume that the social planner charges on every route the marginal cost pricing without knowing what is the efficient equilibrium. The result is a dynamic version of Pigou’s solution, where the implementation is made in a decentralized way and the information about players gathered by the social planner is minimal. Our result and setting may be extended to the general case of negative externalities.