سال انتشار:
2020
عنوان انگلیسی مقاله:
Comparison of competing market mechanisms with reinforcement learning in a carpooling scenario
ترجمه فارسی عنوان مقاله:
مقایسه مکانیزم های بازار رقابت با یادگیری تقویتی در یک سناریو کارپول
منبع:
Sciencedirect - Elsevier - Transportation Research Interdisciplinary Perspectives, 7 (2020) 100190. doi:10.1016/j.trip.2020.100190
نویسنده:
Thomas Pitz, Deniz Kayar ⁎, Wolf Gardian, Jörn Sickmann, Hasan Alkaş
چکیده انگلیسی:
In this paper a multi-agent simulation was implemented to analyze the dynamics of different market mechanisms with
a Reinforcement Learning algorithm in the context of a carpooling market. The agents in the simulation, car owners
(COs) and non car owners (NCOs), had to sell or buy a car seat for multiple rounds by picking one of two possible
mechanisms: Dutch Auction or Fixed Price. In the beginning of the simulation the agents have no information about
the efficiency of these mechanisms and they are chosen with the same probability. In the course of the simulation a
Reinforcement Learning algorithm alters the agents preferences for the two mechanisms depending on their
cumulative payoffs. The key finding is that sellers have a clear preference for the Dutch auction mechanism with
differing degrees dependent on the seller/buyer ratio. Buyers on the other hand have no significant preference for
any mechanism. If these results are replicable, they suggest that an increased utilization of the Dutch auction could
lead to an expansion of the carpooling market, increasing its impact as an alternative means of transportation.
Keywords: Multi-agent simulation | Reinforcement learning | Traffic | Carpooling | Auction | Market
قیمت: رایگان
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