Tentative Schedule: (20 minutes talk + 10 minutes discussion)
14:00 - 14:30 Jürgen Jost: The cognitive geometry of words14:30 - 15:00 Armin Pournaki and Eckehard Olbrich: Document embeddings: from similarity measures to concept spaces15:00 - 15:30 Ivan Yamshchikov: Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric, see abstract15:30 - 16:00 General discussion + Break16:00 - 16:30 Sven Banisch and Tom Willaerts: Tracking causal relations in the news: Data, tools, and models for the analysis of argumentative statements in online media16:30 - 17:00 Guillermo Restrepo: The semiotic system of chemistry and its interplay with the evolution of chemical knowledge17:00 - 17:30 Final discussion
Motives such as affiliation and autonomy orchestrate experience and behavior in order to satisfy psychological needs and protect them from violation (Grawe, 1998). Motives can be in conflict with each other (Epstein, 2003); for example, an individual with an affiliation-autonomy-conflict might experience being part of a group as threat for autonomy, but being alone as violation of his or her need for affiliation. There is evidence that conflicts between motives are accompanied by diminished well-being (e.g., Gray, Ozer, & Rosenthal, 2017), but the underlying dynamics are not well understood. After briefly introducing concepts from motivational psychology, two studies will be presented. In study 1, an agent-based model of intrapersonal conflict between motives (within an individual) is formulated and informed by empirical data from the daily life of students (Westermann, Berger, Steiner, & Banisch, 2017). In study 2, a dynamic system model of interpersonal conflict between affiliation motives (of two individuals) is developed based on equations from population dynamics (Holland & DeAngelis, 2010; Revilla, 2015). The studies are a starting point for a computational clinical psychology that explains the formation and maintenance of psychological problems using empirically informed mathematical modeling and simulation. In addition, the motivational perspective on experience and behavior is expected to be of use for other disciplines that model individual and social behavior (e.g., motive-driven opinion dynamics). ReferencesEpstein, S. (2003). Cognitive-experiential self-theory of personality. In T. Millon & M. J. Lerner (Eds), Comprehensive Handbook of Psychology, Volume 5: Personality and Social Psychology (pp. 159-184). Hoboken, NJ: Wiley & Sons.Grawe, K. (1998). Psychologische Therapie [Psychological therapy]. Hogrefe, Verlag für Psychologie. Gray, J. S., Ozer, D. J., & Rosenthal, R. (2017). Goal conflict and psychological well-being: A meta-analysis. Journal of Research in Personality, 66, 27–37. doi:10.1016/j.jrp.2016.12.003 Holland, J. N., & DeAngelis, D. L. (2010). A consumer-resource approach to the density-dependent population dynamics of mutualism. Ecology, 91(5), 1286-1295. doi:10.1890/09-1163.1 Revilla, T. A. (2015). Numerical responses in resource-based mutualisms: A time scale approach. Journal of Theoretical Biology, 378, 39-46. doi:10.1016/j.jtbi.2015.04.012 Westermann, S., Berger, T., Steiner, F., & Banisch, S. (2017, September). Paper presented at the Social Simulation Conference, Dublin, Ireland. Retrieved from https://www.researchgate.net/publication/321491004
I present a hands-on introduction to the theory of regularity structures by Martin Hairer. This theory provides the machinery for treating of a class of formally ill-posed stochastic partial differential equations, including the KPZ equation which models surface growth. It can be considered a deep extension of the theory of rough paths, and I will sketch out the explicit link. No prior knowledge of rough path theory is necessary. A general acquaintance with (Schwarz) distributions will be helpful.
I present a hands-on introduction to the theory of regularity structures by Martin Hairer. This theory provides the machinery for treating of a class of formally ill-posed stochastic partial differential equations, including the KPZ equation which models surface growth. It can be considered a deep extension of the theory of rough paths, and I will sketch out the explicit link. No prior knowledge of rough path theory is necessary. A general acquaintance with (Schwarz) distributions will be helpful.
I present a hands-on introduction to the theory of regularity structures by Martin Hairer. This theory provides the machinery for treating of a class of formally ill-posed stochastic partial differential equations, including the KPZ equation which models surface growth. It can be considered a deep extension of the theory of rough paths, and I will sketch out the explicit link. No prior knowledge of rough path theory is necessary. A general acquaintance with (Schwarz) distributions will be helpful.
The lectures are meant to give introductions to non-experts, and we shall therefore only treat the basic concepts and ideas and omit many technical subtleties or generalizations.Some useful references are Sanders, Verhulst, Murdock, Averaging methods Pavliotis, Stuart, Multiscale techniquesand for the background, for example Berglund, Gentz, Noise-induced phenomena dal Maso, Gamma-convergence Jost, Dynamical systems Jost, Partial differential equations Jost, Li-Jost, Calculus of variationsand others.
The lectures are meant to give introductions to non-experts, and we shall therefore only treat the basic concepts and ideas and omit many technical subtleties or generalizations.Some useful references are Sanders, Verhulst, Murdock, Averaging methods Pavliotis, Stuart, Multiscale techniquesand for the background, for example Berglund, Gentz, Noise-induced phenomena dal Maso, Gamma-convergence Jost, Dynamical systems Jost, Partial differential equations Jost, Li-Jost, Calculus of variationsand others.
