Émergence | EPFL Graph Search

L’émergence est un concept philosophique formalisé au et qui peut être grossièrement résumé par l'adage : « le tout est plus que la somme des parties ». Il s'oppose au réductionnisme comme aux doctrines dualistes (dualisme ou vitalisme). Une propriété peut être qualifiée d’émergente si elle « découle » de propriétés plus fondamentales tout en demeurant « nouvelle » ou « irréductible » à celles-ci. Ainsi, John Stuart Mill constate que les propriétés de l'eau ne sont pas réductibles à celles de l'hydrogène ou de l'oxygène. Dans le champ des sciences, le concept d'émergence permet de décrire des caractéristiques de la réalité de façon moniste sans tomber dans le réductionnisme. Il traduit le fait que, dans le monde observable (que ce soit pour la matière inerte, les organismes vivants ou le psychisme), la connaissance de phénomènes ne se déduit pas toujours de celle de leurs composants fondamentaux. L'enjeu des divers émergentismes proposés depuis l'apparition de ce concept est préci

Computational Methods for Audio-Visual Analysis of Emergent Leadership in Teams

Dairazalia Sanchez Cortes

Face-to-face interactions are part of everyday life, ranging from family to working in teams and to global communities. Social psychologists have long studied these interactions with the aim of understanding behavior, motivations, and emergence of interaction patterns. An organization is environment rich in daily interactions including structured periodic meetings, planning, brainstorming, negotiations, decision-making and informal gatherings and leaders play a key role in many of them. Leader face problems, propose solutions, make decisions, and often are the main source of inspiration of the employees. Identifying emergent leaders at early stages in organizations is a key issue in organizational behavioral research, and a new problem in social computing. The study of this phenomenon requires sensing of natural face-to-face interactions, automatic extraction of behavioral cues and reliable machine learning algorithms to identify emergent leaders. In this thesis we present a computational approach to analyze emergence of leadership in small groups using multimodal audio and visual features. In the computational framework, we first present an analysis on how an emergent leader is perceived in newly formed, small groups. We present the ELEA (Emergent LEadership Analysis) corpus collected with the aim of analyzing emergence of leaders. We propose to analyze emergent leaders, using a variety of nonverbal cues studied in social psychology and automatically extracted from audio and video streams. Our analysis address how the emergent leader is perceived by his/her peers in terms of speaking and visual active, and its relation with the most dominant person (including external observers’ perception). We then propose to investigate which individual nonverbal channel (or combination of features from different channels) provides better inferences of the emergent leader and related concepts using unsupervised and supervised methods. We use a supervised collective approach which adds relational information to the nonverbal cues and compare its performance, with the performance of supervised (non-collective) and unsupervised methods. We also propose to capture the social visual attention patterns from automatically extracted features from video, in order to analyze who receives or gives the largest amount of visual attention in the group. Finally, with the aim of understanding who receives the largest amount of visual attention while speaking and who has the highest dominance ratio (i.e., many occurrences of looking at others while speaking and few occurrences of looking at others while not speaking). We synchronize the audio and video streams to capture the speaking and attention activity patterns. We end our analysis exploring the impact of the verbal content (language style) in the interactions and its influence in the perception of emergent leaders. For the language style analysis, we propose to compute word categories extracted from manual transcriptions of the discussions as well as from automatically detected keywords. We propose to use a supervised method to obtain the relevant features, and to use only the top word categories to predict the emergent leader and related concepts in each group. We then propose to differentiate word categories, between highly context-related and context-free, to explore the feasibility to infer the emergent leader in a fully automatic approach from the context-free language style. This dissertation address an audio and visual analysis of the ubiquitous phenomenon of emergent leadership in a fully automatic computational approach from face-to-face interactions. The nonverbal behavioral analysis is inspired in previous works on social psychology in the context of emergent leadership and related concepts. The automatically extracted nonverbal features are modeled to feed state-of-the-art machine learning techniques in order to infer emergent leaders.

EPFL2013

Towards sufficiency in housing: Agent-based model and transition scenarios

Margarita Agriantoni

Research problem: Housing is responsible for a considerable part of global resource consumption. In Switzerland, it accounts for almost one third of the country's CO2 emissions and half of the total energy demand. Thus, housing plays an important role in the transition to sustainable development. Housing has been thoroughly studied from a disciplinary perspective, e.g., economics, social sciences, psychology, engineering. However, little attention has been paid to housing as a system of interrelated actors, e.g., developers, owners, tenants and state, whose actions might be described by different disciplines. Aim: The aim of this thesis is to investigate how a change in the construction practices of property owners in combination to a more space-efficient allocation of dwellings to households and a behavioural change of tenants can achieve a substantial reduction in the environmental impact of housing. This dissertation focuses on the interrelations of housing actors, concentrating mainly on the property owners and explores which measures and to what extent can lead to a reduction of space consumption of housing.Methods: Housing is characterised by a high level of complexity, therefore a transdisciplinary approach is adopted. Firstly, the Swiss housing market and its unique attributes are studied. However, in this thesis, we study a subset of the Swiss rental housing market; it comprises two housing cooperatives: ABZ in Zurich and SCHL in Lausanne as well as the insurer and asset manager Swiss Mobiliar. Their housing stocks, of approximately 10,000 dwellings, are examined in depth and are used as a case study. Extensive data gathering allowed to create an exhaustive inventory of the building stock of the three property owners. The data on tenants was limited, thus, we conducted a tenant survey. Furthermore, a series of workshops with both tenants and property owners were organised to study their decision-making processes. A bottom-up agent-based model (ABM) is built, which portrays the case study housing system. The main actors of the rental housing market (property owners and households) are represented in the model by agents; the owner agents make decisions about their building stock and tenants, while the household agents choose a dwelling based on their needs and housing preferences. The dynamic evolution of both owners and households and the interaction between them is simulated in the model and allows the study of emergent phenomena. The present thesis attempts the assessment of the environmental impact of housing through the lens of housing sufficiency. Space consumption, in terms of dwelling surface and floor area per capita, is considered as the largest determinant of resource consumption.Results: The simulation results show that measures taken to decrease the environmental impact of housing and space consumption are inadequate if owners do not change their construction practices and households do not actively change their housing behaviour. Most measures explored in this thesis, if implemented individually, succeed in reducing the rate of increase in space consumption but fail to reverse the upward trend. A more space-efficient allocation of dwellings to households proves to have a certain effect. However, only when combined with other measures, such as the densification of the existing building stock and a change in construction practices, a significant decrease of environmental impact is observed.

EPFL2022

Emergent order in hydrodynamic spin lattices

John Bush, Alexis Marie Frederic Goujon

Macroscale analogues(1-3) of microscopic spin systems offer direct insights into fundamental physical principles, thereby advancing our understanding of synchronization phenomena(4) and informing the design of novel classes of chiral metamaterials(5-7). Here we introduce hydrodynamic spin lattices (HSLs) of 'walking' droplets as a class of active spin systems with particle-wave coupling. HSLs reveal various non-equilibrium symmetry-breaking phenomena, including transitions from antiferromagnetic to ferromagnetic order that can be controlled by varying the lattice geometry and system rotation(8). Theoretical predictions based on a generalized Kuramoto model(4) derived from first principles rationalize our experimental observations, establishing HSLs as a versatile platform for exploring active phase oscillator dynamics. The tunability of HSLs suggests exciting directions for future research, from active spin-wave dynamics to hydrodynamic analogue computation and droplet-based topological insulators. A macroscopic analogue of a spin system is shown to emerge in an ensemble of droplets bouncing on the surface of a vibrating bath, revealing symmetry-breaking phenomena such as 'magnetic' ordering.

NATURE PORTFOLIO2021