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Price of Anarchy in Bernoulli Congestion Games with Affine Costs
arXiv - CS - Computer Science and Game Theory Pub Date : 2019-03-08 , DOI: arxiv-1903.03309
Roberto Cominetti, Marco Scarsini, Marc Schr\"oder, and Nicol\'as Stier-Moses

Since demand in transportation networks is uncertain, commuters need to anticipate different traffic conditions. We capture this uncertainty by assuming that each commuter may make the trip or not with a fixed probability, creating an atomic congestion game with Bernoulli demands. Each commuter participates with an exogenous probability $p_i\in[0,1]$, which is common knowledge, independently of everybody else, or does not travel and incurs no cost. We first prove that the resulting game is potential. Then we compute the parameterized price of anarchy to characterize the impact of demand uncertainty on the efficiency of the transportation network. It turns out that the price of anarchy as a function of the maximum participation probability $p=\max_{i} p_i$ is a nondecreasing function. The worst case is attained when commuters have the same participation probabilities $p_i\equiv p$. For the case of affine costs, we provide an analytic expression for the parameterized price of anarchy as a function of $p$. This function is continuous on $(0,1]$, is equal to $4/3$ for $0

中文翻译:

具有仿射成本的伯努利拥塞博弈中无政府状态的代价

由于交通网络的需求不确定,通勤者需要预测不同的交通状况。我们通过假设每个通勤者可能以固定概率出行或不出行来捕捉这种不确定性,从而创建具有伯努利需求的原子拥堵游戏。每个通勤者以外生概率 $p_i\in[0,1]$ 参与,这是常识,独立于其他所有人,或者不旅行且不产生任何成本。我们首先证明由此产生的游戏是有潜力的。然后我们计算无政府状态的参数化价格来表征需求不确定性对交通网络效率的影响。事实证明,作为最大参与概率 $p=\max_{i} p_i$ 的函数的无政府状态价格是一个非递减函数。当通勤者具有相同的参与概率 $p_i\equiv p$ 时,就会出现最坏的情况。对于仿射成本的情况,我们提供了无政府状态参数化价格的解析表达式,作为 $p$ 的函数。此函数在 $(0,1]$ 上连续,对于 $0 等于 $4/3$
更新日期:2020-03-24
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