We analyze a class of stochastic dynamic games among teams with asymmetric information, where members of a team share their observations internally with a delay of $d$. Each team is associated with a controlled Markov Chain, whose dynamics are coupled through the players' actions. These games exhibit challenges in both theory and practice due to the presence of signaling and the increasing domain of information over time. We develop a general approach to characterize a subset of Nash Equilibria where the agents can use a compressed version of their information, instead of the full information, to choose their actions. We identify two subclasses of strategies: Sufficient Private Information Based (SPIB) strategies, which only compress private information, and Compressed Information Based (CIB) strategies, which compress both common and private information. We show that while SPIB-strategy-based equilibria always exist, the same is not true for CIB-strategy-based equilibria. We develop a backward inductive sequential procedure, whose solution (if it exists) provides a CIB strategy-based equilibrium. We identify some instances where we can guarantee the existence of a solution to the above procedure. Our results highlight the tension among compression of information, existence of (compression based) equilibria, and backward inductive sequential computation of such equilibria in stochastic dynamic games with asymmetric information.
翻译:我们分析一组具有不对称信息的团队之间的随机动态游戏,一个团队的成员在内部分享其观测结果,拖延了美元。每个团队都与一个受控的Markov 链子相关,其动态通过玩家的行动相互配合。这些游戏在理论和实践上都存在挑战,因为信号的存在和信息领域随时间而不断扩大。我们开发了一种通用的方法来描述Nash Equilibria的子集,在那里,代理人可以使用压缩版的信息而不是完整信息来选择行动。我们确定了两个子类的战略:足够的私人信息(SPIB)战略,仅压缩私人信息;压缩信息(CIB)战略。我们找出了某些例子,我们可以保证基于共同信息与私人信息的压缩(CIB)战略。我们显示,虽然基于战略的平衡(Squirib-Reformation-Reformationy-equiliblibraia)的解决方案存在,但对于基于CIB-Requiblegy-econlibrarial 的代理者来说,情况并非如此。我们开发了一种倒退的顺序程序,其解决方案(如果存在的话)提供了基于CIB战略的平衡。我们发现了一些实例,我们可以保证基于稳定的平级信息的平级平级的解决方案在上文中存在。