We introduce a game in which two players with opposing objectives seek to repeatedly takeover a common resource. The resource is modeled as a discrete time dynamical system over which a player can gain control after spending a state-dependent amount of energy at each time step. We use a FlipIT-inspired deterministic model that decides which player is in control at every time step. A player's policy is the probability with which the player should spend energy to gain control at each time step. Our main results are three-fold. First, we present analytic expressions for the cost-to-go as a function of the hybrid state of the system, i.e., the physical state of the dynamical system and the binary \texttt{FlipDyn} state for any general system with arbitrary costs. These expressions are exact when the physical state is also discrete and has finite cardinality. Second, for a continuous physical state with linear dynamics and quadratic costs, we derive expressions for Nash equilibrium (NE). For scalar physical states, we show that the NE depends only on the parameters of the value function and costs, and is independent of the state. Third, we derive an approximate value function for higher dimensional linear systems with quadratic costs. Finally, we illustrate our results through a numerical study on the problem of controlling a linear system in a given environment in the presence of an adversary.
翻译:我们引入了一种游戏, 有两个目标对立的玩家在游戏中试图反复接管共同的资源。 资源以一个离散的时间动态系统为模型, 玩家在每一步花费依赖状态的能量量后就可以控制。 我们使用一个FlipIT 驱动的确定性模型, 以决定玩家在每一步中控制哪个玩家。 玩家的政策是玩家在每一步中花费能量以获得控制权的概率。 我们的主要结果是三倍。 首先, 我们用一个分析性化的表达方式来表达成本到系统混合状态的函数, 即动态系统和二进制状态的物理状态和二进制状态的状态。 我们使用任意成本的状态, 我们使用FlipIT 和二进制的确定性确定性模式来决定任何普通系统。 当玩家在每一个步骤中控制哪个玩家都在控制中。 玩家的政策是玩家在每一步中花费能量来获得控制权的概率的概率。 我们用一个连续的物理状态来计算纳什平衡( NEe) 。 首先, 我们用分析性状态的表达方式, 我们的状态, 我们显示 NEEEEE 仅取决于数值值的参数和数值的参数的参数的参数参数的参数的参数值的参数, 和成本的参数, 以及直径值值的参数, 以及直径值值的值的值的值的值的值的值值值值值值的大小, 。