From: 2025-02-28 14:00 to 14:45
Place: Seminar Room M 3170-73 at Dept. of Automatic Control, LTH
Contact: anders [dot] rantzer [at] control [dot] lth [dot] se

Date & Time: February 28, 14:00-14:45
Location: Seminar Room M 3170-73 at Dept. of Automatic Control, LTH
Speaker: Claudio Altafini
Title: Quantifying leadership in complex negotiation processes: a social
power game

Abstract:  We consider complex multistage multiagent negotiation
processes such as those occurring at climate conferences and ask
ourselves how can an agent maximize its social power, intended as
influence over the outcome of the negotiation. This question can be
framed as a strategic game played over an opinion dynamics model, in
which the action of an agent consists in stubbornly defending its own
opinion. We show that for consensus-seeking opinion dynamics models in
which the interaction weights are uniform, the optimal action obeys to
an early mover advantage principle, i.e., the agents behaving stubbornly
in the early phases of the negotiations achieve the highest social
power. When looking at data collected from the climate change
negotiations going on at the United Nations Framework Convention on
Climate Change, we find evidence of the use of the early mover strategy.
Furthermore, we show that the social powers computed through our model
correlate very well with the perceived leadership roles assessed through
independent survey data.
 

Biography: Claudio Altafini received a Master degree ('Laurea') in Electrical

Engineering from the University of Padova, Italy, in 1996 and a PhD in
Optimization and Systems Theory from the Royal Institute of Technology,
Stockholm, Sweden in 2001. From 2001 till 2013 he was with the
International School for Advanced Studies (SISSA) in Trieste, Italy.
Since 2014 he is a Professor in the Division of Automatic Control, Dept.
of Electrical Engineering at Linkoping University, Sweden. His research
interests are in the areas of nonlinear systems analysis and control,
with applications to complex networks, social networks, systems biology,
and quantum mechanics.