Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Simulating organizations: computational models of institutions and groups
Simulating organizations: computational models of institutions and groups
Multiagent systems: a modern approach to distributed artificial intelligence
Multiagent systems: a modern approach to distributed artificial intelligence
Multiagent systems and societies of agents
Multiagent systems
Understanding Anasazi culture change through agent-based modeling
Dynamics in human and primate societies
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Simulation for the Social Scientist
Simulation for the Social Scientist
Dynamics of Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes
Dynamics of Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes
Density Delay and Organizational Survival: Computational Models and Empirical Comparisons
Computational & Mathematical Organization Theory
Computational & Mathematical Organization Theory
Reinforcement Learning Rules in a Repeated Game
Computational Economics
Creatures: Entertainment Software Agents with Artificial Life
Autonomous Agents and Multi-Agent Systems
Further towards a taxonomy of agent-based simulation models in environmental management
Mathematics and Computers in Simulation - Selected papers of the MSSANZ/IMACS 14th biennial conference on modelling and simulation
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (Handbook of Computational Economics)
Environmental Modelling & Software
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The integrated-environmental, economic and social-analysis of climate change calls for a paradigm shift as it is fundamentally a problem of complex, bottom-up and multi-agent human behaviour. There is a growing awareness that global environmental change dynamics and the related socio-economic implications involve a degree of complexity that requires an innovative modelling of combined social and ecological systems. Climate change policy can no longer be addressed separately from a broader context of adaptation and sustainability strategies. Past research on artificial intelligence and social simulation has developed a promising methodology. Literature on agent-based modelling ABM shows it's potential to couple social and environmental models and incorporate the influence of micro-level decision making in the system dynamics and to study the emergence of collective responses to policies. However, there are few studies that concretely apply this methodology to the study of climate change related issues. The analysis in this paper supports the idea that today ABM is a consolidated interdisciplinary approach for the bottom-up exploration of climate policies, especially because it can take into account adaptive behaviour and heterogeneity of the system's components.