Prospect Theory Multi-Agent Based Simulations for Non-Rational Route Choice Decision Making Modelling
Prospect Theorie basierte Multi-Agenten Simulationen für nicht-rationalle Route Entscheidung Modellierung
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- Simulations (MASim) and non-rational behaviour. This non-rational behaviour is here based on the Prospect Theory [KT79] (PT), which is compared to the rational behaviour in the Expected Utility Theory [vNM07] (EUT). This model was used to design a modified Q-Learning [Wat89, WD92] algorithm. The PT based Q-Learning was then integrated into a proposed agent architecture. Because much attention is given to a limited interpretation of Simon's definition of bounded-rationality, this interpretation is broadened here. Both theories, rationality andSimulations (MASim) and non-rational behaviour. This non-rational behaviour is here based on the Prospect Theory [KT79] (PT), which is compared to the rational behaviour in the Expected Utility Theory [vNM07] (EUT). This model was used to design a modified Q-Learning [Wat89, WD92] algorithm. The PT based Q-Learning was then integrated into a proposed agent architecture. Because much attention is given to a limited interpretation of Simon's definition of bounded-rationality, this interpretation is broadened here. Both theories, rationality and the non-rationality, are compared and the discordance in their results discussed. The main contribution of this work is to show that an alternative is available to the EUT that is more suitable for human decision-makers modelling. The evidences show that rationality is not appropriated for modelling persons. Therefore, instead of fine-tuning the existent model the use of another one is proposed and evaluated. To tackle this, the route choice problem was adopted to perform the experiments. To evaluate the proposed model three traffic scenarios are simulated and their results analysed.…
Autor(en): | Gustavo Kuhn Andriotti |
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URN: | urn:nbn:de:bvb:20-opus-40483 |
Dokumentart: | Dissertation |
Titelverleihende Fakultät: | Universität Würzburg, Fakultät für Mathematik und Informatik |
Institute der Universität: | Fakultät für Mathematik und Informatik / Institut für Informatik |
Datum der Abschlussprüfung: | 20.11.2009 |
Sprache der Veröffentlichung: | Englisch |
Erscheinungsjahr: | 2009 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik |
Normierte Schlagworte (GND): | Mehragentensystem; Bestärkendes Lernen <Künstliche Intelligenz> |
Freie Schlagwort(e): | Q-Learning; Route Entscheidung MASim; Prospect Theory; Q-Learning; Route Choice; Traffic |
Datum der Freischaltung: | 25.11.2009 |
Betreuer: | Prof. Dr. Dietmar Seipel |