Key research themes
1. How can game-theoretic models and evolutionary dynamics inform the design of selfishness-resilient cooperative systems?
This research theme explores methodologies to design cooperative distributed systems resilient to selfish behaviors of nodes. It leverages game theory, including classical and evolutionary approaches, to model, analyze, and predict strategies of selfish nodes and to configure system parameters that promote cooperation despite individual incentives to deviate. The focus is on frameworks and tools that automate or semi-automate these processes, enabling designers to balance resilience and performance across various cooperative system applications.
2. What conceptual frameworks clarify forms and motivations of cooperation in multi-agent and socio-technical systems?
This theme encompasses theoretical analyses and typologies that demarcate cooperation, competition, and coordination in multi-agent settings and socio-technical systems. The focus lies in distinguishing types of cooperative behavior, analyzing emergent and intentional cooperation, and understanding the philosophical, cognitive, and organizational underpinnings that drive cooperation or influence its emergence and sustainability. It informs system design by articulating agent motivations, behavioral assumptions, and system-level implications.
3. How do cooperative optimization and game-theoretic approaches model and enhance multi-agent cooperative and competitive behaviors in distributed systems?
This research area investigates algorithms and frameworks that leverage distributed optimization and game theory to analyze and facilitate cooperation and competition among autonomous agents. It spans static and dynamic games, integrates privacy-aware distributed online optimization and federated learning, and explores solutions such as Nash equilibria and regret matching. This informs the design of efficient, privacy-preserving multi-agent systems that balance global cooperation and individual strategic interests.