Risk Aversion and Coordination in a Simple Stag Hunt Game: Agent Based Modelling

2010 ◽  
Author(s):  
Ch'ng Kean Siang
Keyword(s):  
Risk Aversion ◽  
Agent Based ◽  
Stag Hunt ◽  
Agent Based Modelling ◽  
Stag Hunt Game

scholarly journals Agent-based Modelling and Simulation for Circular Business Model Experimentation

2021 ◽  
pp. 200055
Author(s):  
Kasper P.H. Lange ◽  
Gijsbert Korevaar ◽  
Inge F. Oskam ◽  
Igor Nikolic ◽  
Paulien M. Herder
Keyword(s):  
Business Model ◽  
Modelling And Simulation ◽  
Agent Based ◽  
Agent Based Modelling

scholarly journals Skin Stem Cell Hypotheses and Long Term Clone Survival – Explored Using Agent-based Modelling

2013 ◽  
Vol 3 (1) ◽  
Author(s):  
X. Li ◽  
A. K. Upadhyay ◽  
A. J. Bullock ◽  
T. Dicolandrea ◽  
J. Xu ◽  
...  
Keyword(s):  
Stem Cell ◽  
Agent Based ◽  
Agent Based Modelling

scholarly journals Visualising Ostia’s Processional Landscape Through a Multi-Layered Computational Approach: Case Study of the Cult of the Magna Mater

2019 ◽  
Vol 5 (1) ◽  
pp. 444-467
Author(s):  
Katherine A. Crawford
Keyword(s):  
Network Analysis ◽  
Computational Approach ◽  
Urban Network ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Existing Problems ◽  
Layered Approach ◽  
Religious Landscape ◽  
Insight Into

AbstractOstia, the ancient port of Rome, had a rich religious landscape. How processional rituals further contributed to this landscape, however, has seen little consideration. This is largely due to a lack of evidence that attests to the routes taken by processional rituals. The present study aims to address existing problems in studying processions by questioning what factors motivated processional movement routes. A novel computational approach that integrates GIS, urban network analysis, and agent-based modelling is introduced. This multi-layered approach is used to question how spectators served as attractors in the creation of a processional landscape using Ostia’s Campo della Magna Mater as a case study. The analysis of these results is subsequently used to gain new insight into how a greater processional landscape was created surrounding the sanctuary of the Magna Mater.

scholarly journals Evolution of social learning when high expected payoffs are associated with high risk of failure

2011 ◽  
Vol 8 (64) ◽  
pp. 1604-1615 ◽  
Author(s):  
Michal Arbilly ◽  
Uzi Motro ◽  
Marcus W. Feldman ◽  
Arnon Lotem
Keyword(s):  
High Risk ◽  
Social Learning ◽  
Risk Aversion ◽  
Individual Risk ◽  
Individual Experience ◽  
Agent Based ◽  
Risk Of Failure ◽  
Expected Payoffs ◽  
Maladaptive Behaviours ◽  
Optimal Behaviour

In an environment where the availability of resources sought by a forager varies greatly, individual foraging is likely to be associated with a high risk of failure. Foragers that learn where the best sources of food are located are likely to develop risk aversion, causing them to avoid the patches that are in fact the best; the result is sub-optimal behaviour. Yet, foragers living in a group may not only learn by themselves, but also by observing others. Using evolutionary agent-based computer simulations of a social foraging game, we show that in an environment where the most productive resources occur with the lowest probability, socially acquired information is strongly favoured over individual experience. While social learning is usually regarded as beneficial because it filters out maladaptive behaviours, the advantage of social learning in a risky environment stems from the fact that it allows risk aversion to be circumvented and the best food source to be revisited despite repeated failures. Our results demonstrate that the consequences of individual risk aversion may be better understood within a social context and suggest one possible explanation for the strong preference for social information over individual experience often observed in both humans and animals.

A Comparison between Agent-Based and GIS-Based Tsunami Evacuation Simulations: A Case Study for Tofino, BC

2021 ◽  
Author(s):  
Joseph Kim ◽  
Tomoyuki Takabatake ◽  
Ioan NISTOR ◽  
Tomoya Shibayama
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Mortality Rates ◽  
Geographical Information ◽  
Evacuation Planning ◽  
Loss Of Life ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Validation Tool

Soft measures such as evacuation planning are recommended to mitigate the loss of life during tsunamis. Two types of evacuation models are widely used: (1) Agent-based modelling (ABM) defines sets of rules that individual agents in a simulation follow during a simulated evacuation. (2) Geographical information systems (GIS) are more accessible to city planners, but cannot incorporate the dynamic behaviours found in ABMs. The two evacuation modelling methodologies were compared through a case study by assessing the state of evacuation preparedness and investigating potential mitigation options. The two models showed different magnitudes for mortality rates and facility demand but had similar trends. Both models agreed on the best solution to reduce the loss of life for the community. GIS may serve as a useful tool for initial investigation or as a validation tool for ABMs. ABMs are recommended for use when modelling evacuation until GIS methodologies are further developed.

Agent-based modelling of car platooning for traffic optimization

2021 ◽  
Author(s):  
Michal Lemiec ◽  
Karol Malinowski ◽  
Mateusz Szymonski ◽  
Maria Ganzha ◽  
Marcin Paprzycki
Keyword(s):  
Agent Based ◽  
Agent Based Modelling ◽  
Traffic Optimization
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