SOAR: an architecture for general intelligence
Artificial Intelligence
Readings in uncertain reasoning
Readings in uncertain reasoning
Would-be worlds: how simulation is changing the frontiers of science
Would-be worlds: how simulation is changing the frontiers of science
Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Team soar: a model for team decision making
Simulating organizations
Simulation for the Social Scientist
Simulation for the Social Scientist
Design patterns from biology for distributed computing
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Guest editors' introduction, special issue on environments for multi-agent systems
Autonomous Agents and Multi-Agent Systems
Environment as a first class abstraction in multiagent systems
Autonomous Agents and Multi-Agent Systems
Agent communication and social concepts
Autonomous Agents and Multi-Agent Systems
Agent communication and artificial institutions
Autonomous Agents and Multi-Agent Systems
A cognitive social agent architecture for cooperation in social simulations
IVA'12 Proceedings of the 12th international conference on Intelligent Virtual Agents
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This paper argues that the agent-based simulation approach is just the one appropriate to the social sciences (including economics). Although there were many predecessor approaches, which tried to build formal models of social systems, all of them fell short of the peculiar features of the objects of all social sciences: complex systems consisting of numerous autonomous actors who interact with each other, who take on different roles at the same time, who are conscious of their interactions and roles and who can communicate with the help of symbolic languages even about the counterfactual. These human actors are unlike physical particles although their behaviour might sometimes be quite similar to the behaviour of physical particles when humans occur in very large numbers (but they are most interesting when they form only small networks). Real human actors would not concede that their behaviour is stochastic, they will always assert that their actions are deliberate (but at the same time these actions are not entirely predictable). Human actors are not entirely rational although their behaviour might sometimes seem as if they were (but they are most interesting when their rationality is only bounded and when their payoff is multidimensional). Social systems seem to be the most adaptive systems that we know about, and this is why we could perhaps use them as patterns for artificial adaptive systems --- and if we knew enough about the modes of operations of human social systems, social sciences could even contribute to agent-based modelling in other fields.