Search Results for author: Mariana Macedo

Found 5 papers, 2 papers with code

Measuring and Controlling Divisiveness in Rank Aggregation

1 code implementation14 Jun 2023 Rachael Colley, Umberto Grandi, César Hidalgo, Mariana Macedo, Carlos Navarrete

In rank aggregation, members of a population rank issues to decide which are collectively preferred.

Decision Making

Differences in the spatial landscape of urban mobility: gender and socioeconomic perspectives

1 code implementation12 Feb 2021 Mariana Macedo, Laura Lotero, Alessio Cardillo, Ronaldo Menezes, Hugo Barbosa

Many of our routines and activities are linked to our ability to move; be it commuting to work, shopping for groceries, or meeting friends.

Physics and Society Computers and Society

Gender Patterns of Human Mobility in Colombia: Reexamining Ravenstein's Laws of Migration

no code implementations29 Nov 2019 Mariana Macedo, Laura Lotero, Alessio Cardillo, Hugo Barbosa, Ronaldo Menezes

Public stakeholders implement several policies and regulations to tackle gender gaps, fostering the change in the cultural constructs associated with gender.

Social and Information Networks Physics and Society

Characterizing the Social Interactions in the Artificial Bee Colony Algorithm

no code implementations8 Apr 2019 Lydia Taw, Nishant Gurrapadi, Mariana Macedo, Marcos Oliveira, Diego Pinheiro, Carmelo Bastos-Filho, Ronaldo Menezes

Recent advances in the literature, however, have proposed to study these systems via the network that emerges from the social interactions within the swarm (i. e., the interaction network).

Uncovering the Social Interaction in Swarm Intelligence with Network Science

no code implementations8 Nov 2018 Marcos Oliveira, Diego Pinheiro, Mariana Macedo, Carmelo Bastos-Filho, Ronaldo Menezes

Here, we address this gap by introducing a network-based framework---the interaction network---to examine computational swarm-based systems via the optics of the social dynamics of such interaction network; a clear example of network science being applied to bring further clarity to a complicated field within artificial intelligence.

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