Simulating Human Behavior for Understanding and Managing Environmental Resource Use

Abstract

Computer simulation allows for the experimental study of dynamic interactions between human behavior and complex environmental systems. Behavioral determinants and processes as identified in social-scientific theory may be formalized in simulated agents to obtain a better understanding of man-environment interactions and of policy measures aimed at managing these interactions. A number of exemplary agent-based simulation studies is discussed to demonstrate how simu-lations can be used to identify behavioral determinants and processes underlying environmental problems, and to explore the possible effects of policy strategies. Finally, we highlight how agent-based simulation may contribute to our understanding of the dynamics of environmental resources, and how to manage them in a sustainable way.

Complexity and Artificial Markets

“…Aspects such as personality and attitude are considered as well, see for example Jager and Mosler (2007). Hampden-Turner and Trompenaars, 1997) describe cultural differences and their effect on trade at the individual level.…”

Agent-based modelling for planning support of local residential policy in Kanazawa city, Japan

“…Finally the probability for household i choosing location s follows a logistic function showed in (8). Q is means the probability of household i choose location s, which will further be influenced by the utility offered by location s and without considering the unobserved random influences.…”

“…As proved by exist research, ABM is expected to contribute significantly to the study of behavior-environment interactions, and to provide a valuable tool for exploring the effectiveness of policy measures in complex environments [8]. Some researchers in this filed focus on assessment of future socio-ecological consequences resulting from land-use policies [9].…”

Psychology's essential role in alleviating the impacts of climate change.

“…Jager and Mosler (2007) are amongst those who use modeling to understand the outcomes of different policy choices. This form of active modeling offers the attractive advantage of trying out various policies before they are implemented and understanding why they might or might not work, thereby potentially avoiding expensive mistakes in policy-making.…”