Yailen Martínez Jiménez
Multi-Agent Reinforcement Learning tool for Job Shop Scheduling Problems
We propose a user friendly Multi-Agent Reinforcement Learning tool, more appealing for industry. It allows to interact with learning algorithms in such a way that additional constraints can be included and the objectives can be adapted to real world scenarios. The user can keep the schedule obtained or adjust it fixing some operations in order to meet certain constraints, then the tool will optimize the modified solution respecting these preferences.
Yailen Martínez is currently the head of the Computer Science Department at UCLV, where she studied Computer Science and afterwards did a Master in Computer Sciences. She then moved to the Vrije Universiteit Brussel, where she did a master after master and from 2008 to 2012 she was a PhD student, after that she has been working on projects between both universities.