Stackelberg Punishment and Bully-Proofing Autonomous Vehicles
Stackelberg Punishment and Bully-Proofing Autonomous Vehicles
复制标题
Stackelberg 惩罚和防欺凌自动驾驶汽车
DOI：
10.1007/978-3-030-35888-4_34
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Littman, Michael L.
中科院分区：
文献类型：
--
作者：
Cooper, Matt;Lee, Jun Ki;Beck, Jacob;Fishman, Joshua D.;Gillett, Michael;Papakipos, Zoe;Zhang, Aaron;Ramos, Jerome;Shah, Aansh;Littman, Michael L.
重复博弈中的互惠行为可以通过惩罚的威胁来强制实施，正如博弈论著名的“民间定理”所体现的那样。然而，对于一个玩家来说，产生这些阻碍是有代价的。在这项工作中，我们试图通过计算“Stackelberg惩罚”来最小化这一成本，即玩家选择一种行为来充分惩罚另一名玩家，同时在假设另一名玩家会采取最佳反应的情况下最大化自己的分数。这一观点概括了斯塔克尔伯格均衡的概念。已知的用于计算Stackelberg均衡的高效算法可以适用于有效地产生Stackelberg惩罚。我们在一个涉及虚拟自动驾驶汽车和人类参与者的实验中演示了这个想法的应用。我们发现，在需要社会谈判的驾驶场景中，带有Stackelberg惩罚政策的自动驾驶汽车可以阻止人类司机欺凌他人。
Mutually beneficial behavior in repeated games can be enforced via the threat of punishment, as enshrined in game theory’s well-known “folk theorem.” There is a cost, however, to a player for generating these disincentives. In this work, we seek to minimize this cost by computing a “Stackelberg punishment,” in which the player selects a behavior that sufficiently punishes the other player while maximizing its own score under the assumption that the other player will adopt a best response. This idea generalizes the concept of a Stackelberg equilibrium. Known efficient algorithms for computing a Stackelberg equilibrium can be adapted to efficiently produce a Stackelberg punishment. We demonstrate an application of this idea in an experiment involving a virtual autonomous vehicle and human participants. We find that a self-driving car with a Stackelberg punishment policy discourages human drivers from bullying in a driving scenario requiring social negotiation.
无人驾驶汽车会梦见电子羊吗？
DOI：
--
发表时间：
2016
期刊：
影响因子：
--
作者：
Simon Chesterman
通讯作者：
Simon Chesterman
DOI：
--
发表时间：
2008
期刊：
影响因子：
--
作者：
I. Nourbakhsh;R. Simmons;F. Broz
通讯作者：
F. Broz