Game-Of-Goals: Using adversarial games to achieve strategic resilience
Aditya Ghose, Asjad Khan
TL;DR
The paper addresses strategic decision-making under adversarial conditions by modeling an organization’s strategy as a two-player perfect-information game and solving for resilient execution plans via game-tree search. It introduces augmented game trees with state and action nodes, non-deterministic state updates through a Possible Worlds Approach, and goal-model constraints that guide OR/AND refinements to determine robust subgoals. The authors compare Minimax with Alpha-Beta pruning, Monte Carlo Tree Search, and a stochastic baseline, analyzing how depth, simulation count, and branching affect performance. They find that Minimax is exhaustive but computationally expensive, MCTS offers scalable and efficient planning, and stochastic models are fast but may sacrifice accuracy, offering practical guidance for deploying adversarial decision-making in dynamic business contexts.
Abstract
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.