|
Exploiting coalitional games and power indices in movement analysis and centrality/leadership evaluation: An overview and some focus problems| title | Exploiting coalitional games and power indices in movement analysis and centrality/leadership evaluation: An overview and some focus problems |
|---|
| start_date | 2022/06/23 |
|---|
| schedule | 14h |
|---|
| online | no |
|---|
| summary | In this talk Iillustrate a mathematical model and a computational method to automaticallyinvestigate: i) the perception of the origin of full-body human movement andits propagation and ii) the emergence of leadership in social groups. The approach is based on a mathematical gamebuilt over suitably-defined graph structures.
In the case of movement analysis, the graph isinduced by the human body and the players of the game are subset of body joints. Since each vertex contributesto a shared goal (i.e., to the way in which a specific movement-related featureis transferred among the joints), a cooperative game-theoretical model(specifically, a transferable utility game) is adopted. The relevance of thevarious joints in human movement are estimated via the Shapley value - a “powerindex” of mathematical game theory. The method is theoretically investigatedand applied to a motion capture dataset obtained from subjects who performedexpressive movements. Finally, it is validated through an online survey, toshow the capability of the proposed approach to represent the evolution of themost important joint responsible for originating each dancer’s movement.
In the study of leadership, the test-bed is represented by ensemble music performance,where a conductor visibly drives a group of musicians with a set hierarchy andconfiguration. Social interaction and adaptation occurring between musicians,musicians and conductor, and musicians and audience can be investigated throughthe ways in which people adapt their behavior to one another using implicit andexplicit signals through visual, auditory and kinematic channels. The orchestra is represented as a network, wherethe nodes are the conductor and the musicians. The weighted connections betweenpairs of nodes provide a measure of the “degree of similarity” and the “degreeof influence” between each pair of nodes. A cooperative mathematical game isbuilt on such a network, and the Shapley value is used to estimate the degreeof leadership of its nodes.
Finally,in the talk I shortly refer to some other topic of my research on machinelearning, to further stimulate possible new collaborations. |
|---|
| responsibles | Marin |
|---|
Workflow history| from state (1) | to state | comment | date |
|---|
| submitted | published | | 2022/06/16 09:47 UTC |
| |
|