Dr. Mauro Vallati is a Senior Lecturer at the School of Computing and Engineering of the University of Huddersfield (UK). Previously, (2011-2012) he worked as a Research Fellow at the University of Brescia (Italy). He received his Ph.D. in 2012 by the University of Brescia with a thesis on innovative techniques for learning for automated planning. He has been Visiting Researcher at the University of British Columbia (Canada), Delft Technical University (The Netherlands), Universidad National del Sur (Argentina), and National Institute of Informatics (Japan).
His main research interests are in Artificial Intelligence Planning and Argumentation. In particular, he works on domain-independent planning, knowledge engineering, SATisfiability, machine learning, abstract argumentation, portfolio approaches, heuristic search, and automatic algorithm configuration. He is also active in the fields of innovative applications of AI in Medicine, Intelligent Transportation Systems, and Computational Creativity.
Mauro Vallati is a member of the ACM SIGAI (ACM Special Interest Group on Artificial Intelligence) and an ACM Distinguished Speaker. Check also his website: http://maurovallati.blogspot.com
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Knowledge Configuration for AI solvers
Given an off-the-shelf solver and a symbolic representation of a problem to be solved, a way for improving performance is the configuration of the parameters of the solver. Such parameters allow...
Knowledge Engineering for AI Planning
Automated Planning is one of the most prominent AI challenges; it has been studied extensively for several decades and led to numerous real-world applications. Recently, Automated Planning...
Planning and Scheduling Approaches for Urban Traffic Control
The current increase in urbanisation, coupled with the socio-economic motivation for increasing mobility, is pushing the transport infrastructure well beyond its capacity. Traditional urban...
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