Collective reasoning on multi-agent debates
: A coherent approach

Student thesis: Doctoral ThesisDoctor of Philosophy


Currently, the Internet and its virtual platforms are the primary forms of communication in our lives. From international to local communities, citizens search for and demand better ways to express their opinion and decide collectively about the world they live in. However, current collective decision making methods have yet to improve to achieve their potential.

Inspired by e-participation systems, that is, online processes involving government and citizens, this dissertation explores multi-agent debates and collective reasoning. We present three novel approaches to represent a multi-agent debate —the Target oriented discussion framework, the Relational model and the Abstract multi-agent debate— and we use them to study collective reasoning methods. The use of dependencies within a debate and coherence, a notion to capture opinion consistency, play a key role through out this research.

The Target oriented discussion framework structures an argumentation-based debate allowing both positive and negative relationships between the arguments and making it possible for participants to express their opinions about the arguments. In particular, it addresses the problem of how participants can reach an agreement about a single issue being discussed. Several new methods to reach a collective decision are assessed by means of social choice properties. Further to the analysis, a computational assessment shows their applicability in real scenarios.

The Relational model overcomes drawbacks of existing approaches by leaving aside arguments and attack and defence notions to arrange a more general representation of a multi-agent debate. This model clearly distinguishes between different features composing a debate while offering more expressiveness to participants. A family of new opinion aggregation functions is defined, and an exhaustive analysis of their performance regarding their social choice properties is provided. Additionally, a computational analysis demonstrates that collective opinions can be computed efficiently for real-sized debates.

Finally, the Abstract multi-agent debate model extends the notion of a multi-agent debate allowing it to be an abstraction for different approaches. After proving its capability to represent other debate models, we introduce an approach to analyse the quality of a multi-agent debate.

Date of Award1 Sept 2022
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorSimon Parsons (Supervisor) & Natalia Criado Pacheco (Supervisor)

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