Knaster-Tarski's theorem, characterising the greatest fixpoint of a monotone function over a complete lattice as the largest post-fixpoint, naturally leads to the so-called coinduction proof principle for showing that some element is below the greatest fixpoint (e.g., for providing bisimilarity witnesses). The dual principle, used for showing that an element is above the least fixpoint, is related to inductive invariants. In this paper we provide proof rules which are similar in spirit but for showing that an element is above the greatest fixpoint or, dually, below the least fixpoint. The theory is developed for non-expansive monotone functions on suitable lattices of the form $\mathbb{M}^Y$, where $Y$ is a finite set and $\mathbb{M}$ an MV-algebra, and it is based on the construction of (finitary) approximations of the original functions. We show that our theory applies to a wide range of examples, including termination probabilities, metric transition systems, behavioural distances for probabilistic automata and bisimilarity. Moreover it allows us to determine original algorithms for solving simple stochastic games.
翻译:Knaster-Tarski定理将单调函数在完备格上的最大的不动点特征化为最大的后不动点,自然地引出了所谓的协同归纳证明原则,用于展示某些元素位于最大的不动点以下(例如,为提供双模拟见证)。用于展示一个元素位于最小的不动点以上的对偶原理与归纳不变量相关。在本文中,我们提供了类似于这种证明原则的证明规则,用于展示某些元素位于最大的不动点以上或,对偶地,在最小的不动点以下。所开发的理论适用于适合形式的格子$\mathbb{M}^Y$上的非扩张单调函数,其中$Y$是有限集,$\mathbb{M}$是MV代数,基于构造原始函数的(有限)逼近。我们显示了我们的理论适用于广泛的例子,包括终止概率、度量过渡系统、概率自动机的行为距离和双模拟。此外,它允许我们确定用于解决简单随机游戏的原始算法。