My current focus is researching how to coordinate distributed decisions within organisations, so artificial intelligence can improve collective outcomes rather than optimise isolated tasks or departments. I am interested in connecting business management with intelligent-systems research.
I am exploring how strategic goals interact with operational decisions, incentives and middle-manager autonomy. Mathematical optimisation, game theory, multi-agent systems, reinforcement learning, Decision Intelligence and digital twins offer tools to study these interactions; defining priorities and responsibilities remains an organisational choice.
I use examples from people management and Workforce Management, although these questions apply across many business functions. The question guiding this work is: which decisions should a company centralise, and where can AI expand autonomy without losing coordination?
Read the opening essay in this series →My doctoral thesis, completed at the Universidad de Castilla-La Mancha in 2012, focused on distributed control architectures combining multi-agent systems, BDI cognitive models and RFID/EPCIS visibility frameworks to support real-time decisions in logistics and airport environments.
The open-source MAS-DUO library is a Python re-implementation, still in progress, built on PettingZoo AEC to bring the thesis concepts into executable code.