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Andreas Flache

dblp:17/3074 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2010
0000-0002-8276-8819ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Graphics, computer vision, multimedia, augmented reality and games · 2Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Multi-agent systems · 75% Probabilistic and Bayesian machine learning · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Probabilistic and Bayesian machine learning
clustering
0.112005
The Role of Clustering on the Emergence of Efficient Social Conventions · IJCAI 2005
Knowledge, reasoning and agents › Multi-agent systems › normative multi-agent systems › social norms
convention formation
0.112005
The Role of Clustering on the Emergence of Efficient Social Conventions · IJCAI 2005
Knowledge, reasoning and agents › Multi-agent systems
multi-agent coordination
0.112005
The Role of Clustering on the Emergence of Efficient Social Conventions · IJCAI 2005
Knowledge, reasoning and agents › Multi-agent systems › normative multi-agent systems
social norms
0.112005
The Role of Clustering on the Emergence of Efficient Social Conventions · IJCAI 2005
YearPublicationVenuePosition
2010 Individualization as Driving Force of Clustering Phenomena in Humans
abstract
One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals self-organize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict "monoculture" in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in human societies. Strikingly, model predictions are not only robust to "noise"-randomness is actually the central mechanism that sustains pluralism and clustering.
Michael Mäs, Andreas Flache, Dirk Helbing
PLoS Comput. Biol.2
2005 The Role of Clustering on the Emergence of Efficient Social Conventions
Josep M. Pujol, Jordi Delgado, Ramon Sangüesa, Andreas Flache
IJCAI4
2004 Emergence of Complex Networks through Local Optimization
Josep M. Pujol, Andreas Flache, Ramon Sangüesa, Jordi Delgado
ECAI2