Team : SMA
Departure date : 06/05/2015
: Nicolas MAUDET
Influence in Combinatorial and Collective Decision-Making
Influence study in combinatorial and collective decision-making, is an interdisciplinary research area combining computer science and social science, especially artificial intelligence and collective decision-making. Influence has long been studied, for instance in political science, but in the context of combinatorial and collective decision-making, this calls for a study of how influences work among multi-agents and multi-issues, how influences and decision-making are interleaved, and how the structures of influence among agents and issues produce an effect. In the thesis, we mainly performed three aspects of work:
1/ we built complex models of influence based on preference representation languages and social influence models, proposed a series of new patterns of influence to better describe the complex influences in real-world situation, and discussed a series of theoretical problems of influencing and influenced structure (influence from more than one origins, and influence with abstentions and constraints).
2/ we tested the models of influence from an exemplary perspective for interdisciplinary study, from both social science and computer science paradigms, by both qualitative case studies approach and quantitative approaches, to provide an evaluation for the models of influence.
3/ we used the models of influence to perform agent-based simulations, by the example UN Security Council voting. We design those experiments from both social and computer science perspectives, and discuss the interleaved effects between new cases of influence and different SC reform schemes.
: 06/05/2015 - 09h30