Game-Of-Goals: Using adversarial games to achieve strategic resilience

TL;DR

This paper introduces a game-theoretic approach using adversarial game tree search methods to develop resilient strategic plans that are resistant to competitor actions, enhancing organizational robustness.

Contribution

It proposes a novel machinery that applies game tree search techniques to select optimal, defensible strategies for achieving organizational goals under adversarial conditions.

Findings

Effective strategy selection via minimax improves goal achievement.

Evaluation function minimizes adversarial impact on plans.

Method enhances strategic resilience against competitors.

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.