The Multi-Agent Systems (MAS) Group carries out fundamental research on how to model and design intelligent systems that emerge from the interaction of different agents, human and/or artificial. Our research focuses on:
- Logical and computational models of higher-order social cognition to enhance the development of intelligent interaction between people and computer systems, by supporting their abilities to reason about one another. This has applications to among others systems that help to detect deception and understand the spread of fake news in social networks.
- Formal and computational models of argument and their application in AI and in law. An important aim is to investigate responsible hybrid systems that connect knowledge representation and reasoning techniques with the powers of machine learning.
- Computational models of group decision-making processes, such as voting and deliberation, to support the development of more effective decision-making mechanisms with applications to, among others, Blockchain and eDemocracy.