6533b85afe1ef96bd12b97e9
RESEARCH PRODUCT
Evolutionary Game Dynamics for Collective Decision Making in Structured and Unstructured Environments
Dario BausoLeonardo Stellasubject
Equilibrium pointNon-cooperative gamebusiness.industry020208 electrical & electronic engineeringStability (learning theory)Opinion DynamicContext (language use)02 engineering and technologyComplex networkMulti-Agent SystemsGroup decision-makingCompetition (economics)Game TheorySettore ING-INF/04 - AutomaticaControl and Systems Engineering0202 electrical engineering electronic engineering information engineeringEconomicsSocial Network020201 artificial intelligence & image processingPairwise comparisonArtificial intelligenceSettore MAT/09 - Ricerca OperativabusinessMathematical economicsdescription
Abstract For a large population of players we consider a collective decision making process with three possible choices: option A or B or no option. The more popular option is more likely to be chosen by uncommitted players and cross-inhibitory signals can be sent to attract players committed to a different option. This model originates in the context of honeybees swarms, and we generalise it to accommodate other applications such as duopolistic competition and opinion dynamics. The first contribution is an evolutionary game model and a corresponding new game dynamics called expected gain pairwise comparison dynamics explaining how the strategic behaviour of the players may lead to deadlocks or consensus. The second contribution is the study of equilibrium points and stability in the case of symmetric or asymmetric cross-inhibitory signals. The third contribution is the extension of the results to the case of structured environment in which the players are modelled via a complex network with heterogeneous connectivity.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2017-07-01 | IFAC-PapersOnLine |