Goal-Driven Adversarial Search for Distributed Self-Adaptive Systems

Resilience and antifragility are highly desirable properties for systems operating in dynamic, contested environments. Recent work has proposed an approach for achieving antifragility through three new self-? properties, one of which is adversarial self-exploration. In that approach, a single agent is responsible for defending a (distributed) managed system against an adversary. However, a major limitation is that the agent requires full observability of the managed system and its environment, which is not practical in many scenarios-including when a system operates in contested environments. We address this limitation by extending the approach to multi-Agent self-exploration, where agents with partial observability and control of the managed system coordinate with other agents to compute the most resilient responses in the presence of adversaries. We demonstrate the feasibility and scalability of the proposed approach through extensive experimentation.