用对抗博弈提升战略计划的抗干扰能力
Game-Of-Goals: Using adversarial games to achieve strategic resilience
- 基于极大极小算法构建对抗性策略搜索框架
- 通过评估函数选择最抗干扰的执行路径，最小化对手可破坏空间
- 适合需应对恶意竞争者的战略规划场景
本文旨在构建一种使组织战略计划对竞争者行为具备韧性（resilient）的机制。假设给定目标树表示战略目标（也可视为软件系统的需求），且竞争者以最大对抗性方式行动（即针对我们的子目标或整体目标采取对立行动）。我们采用博弈树搜索方法（如极大极小算法）在特定时刻选择最优执行策略，以最大化实现高层战略目标的可能性。该机制通过评估函数比较不同执行策略，帮助我们决定应走哪条路径以获得最佳最终结果。评估函数的核心思想是：使执行计划具有可防御性（defensible），即选择那些使对手可施加阻碍或损害的空间最小化的策略，从而确保战略方案在未来更具鲁棒性。
原文摘要 · Abstract (English)
Our objective in this paper is to develop a machinery that makes a given organizational strategic plan resilient to the actions of competitor agents (adverse environmental actions). We assume that we are given a goal tree representing strategic goals (can also be seen business requirements for a software systems) with the assumption that competitor agents are behaving in a maximally adversarial fashion(opposing actions against our sub goals or goals in general). We use game tree search methods (such as minimax) to select an optimal execution strategy(at a given point in time), such that it can maximize our chances of achieving our (high level) strategic goals. Our machinery helps us determine which path to follow(strategy selection) to achieve the best end outcome. This is done by comparing alternative execution strategies available to us via an evaluation function. Our evaluation function is based on the idea that we want to make our execution plans defensible(future-proof) by selecting execution strategies that make us least vulnerable to adversarial actions by the competitor agents. i.e we want to select an execution strategy such that its leaves minimum room(or options) for the adversary to cause impediment/damage to our business goals/plans.
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