With Machine Learning and Artificial Intelligence now delivering some of the most sought-after tools in a variety of applications, in this talk we will explore machine learning and data analytics techniques for single autonomous agents all the way to multi-agent systems. We will discuss the application of advanced modelling techniques to comprehend complex multi-agent systems, where uncertainty and strategic interactions abound. Additionally, we share insights from our work, illustrating the strategic use of data science to optimize decision-making for intelligent agents.

 

These tools not only empower us to navigate intricate systems but also play a key role in shaping dynamic environments such as economies and societies. The impact extends to decision-making and policy formation, with a specific focus on domains like smart cities, electronic marketplaces, personalised health and beyond

Dr Maria Chli (MEng Computing & PhD Intelligent Systems, Imperial College London) is a Reader in Applied Artificial Intelligence and Robotics at Aston University. She is also the Director of Aston's Computer Science Industry Club, driving application of cutting-edge research in collaboration with the industry.
With over 17 years of experience, Maria's research focus lies in intelligent agents and multi-agent systems. Her core work involves modelling complex systems and optimizing them through the fusion of multi-agent system techniques with machine and deep learning. This entails employing data analytics to discover the characteristics of the entities and systems being modelled and match the behaviour of the simulation to that of the real world.

 

Maria's contributions extend to employing predictive analytics for optimizing decision-making for intelligent agents in a multitude of settings e.g. smart cities, health, fintech.

 

Maria’s team’s ground-breaking work has been recognised through a diverse portfolio of fund awards (EU, Innovate UK, Royal Society) and success in research competitions (e.g., PowerTAC). Notably, their contributions to autonomous traffic control attracted the attention of transport stakeholders. They are being implemented in several real-life transport settings, and have received widespread media coverage, including features on BBC News, Deutsche Welle, and other outlets.

 

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About the EuroCC-2 project

EuroCC 2 will work to identify and address the skills gaps in the European High Performance Computing (HPC) ecosystem and coordinate cooperation across Europe to ensure a consistent skills base.

The role of EuroCC 2 is to establish and run a network of more than 30 NCCs across the EuroHPC Participating States. The NCCs act as single points of access in each country between stakeholders and national and EuroHPC systems. They operate on a regional and national level to liaise with local communities, in particular SMEs, map HPC competencies and facilitate access to European HPC resources for users from the private and public sector.

EuroCC 2 delivers training, interacts with industry, develops competence mapping and communication materials and activities, and supports the adoption of HPC services in other related fields, such as quantum computing, artificial intelligence (AI), high performance data analytics (HPDA) to expand the HPC user base.

 

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This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101101903. The JU receives support from the European Union’s programme Digital Europe and Germany, Bulgaria, Austria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, France, Netherlands, Belgium, Luxembourg , Slovakia, Norway, Switzerland, Turkey, the Republic of North Macedonia, Iceland, Montenegro and Serbia. 

 

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