Conference Paper

A multi-agent simulation using cultural algorithms: The effect of culture on the resilience of social systems

Sch. of Comput. Sci., Windsor Univ., Ont., Canada
DOI: 10.1109/CEC.2003.1299917 Conference: Evolutionary Computation, 2003. CEC '03. The 2003 Congress on, Volume: 3
Source: IEEE Xplore


Explanations for the collapse of complex social systems including social, political, and economic factors have been suggested. Here we add cultural factors into an agent-based model developed by Kohler for the Mesa Verde Prehispanic Pueblo region. We employ a framework for modeling cultural evolution, cultural algorithms developed by Reynolds (1979). Our approach investigates the impact that the emergent properties of a complex system will have on its resiliency as well as on its potential for collapse. That is, if the system's social structure is brittle, any factor that is able to exploit this fragility can cause a collapse of the system. In particular, we will investigate the impact that environmental variability in the Mesa Verde had on the formation of social networks among agents. Specifically we look at how the spatial distribution of rainfall impacts the systems structure. We show that the distribution of agricultural resources is conducive to the generation of so called "small world" networks that require "conduits" or some agents of larger interconnectivity to link the small worlds together. Experiments show that there is a major decrease in these conduits in early 1200 A.D. This can have s serious potential impact on the networks resiliency. While the simulation shows an upturn near the start of the 14th century it is possible that the damage to the network had already been done.

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Available from: Tim Kohler
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    • "The household (agent) rules for marriage and kinship dynamics were described in earlier work [5]–[9]. The social network is defined as the set of all kinship links. "
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    ABSTRACT: In this paper, we use principles from game theory, computer gaming, and evolutionary computation to produce a framework for investigating one of the great mysteries of the ancient Americas: why did the pre-Hispanic Pueblo (Anasazi) peoples leave large portions of their territories in the late A.D. 1200s? The gaming concept is overlaid on a large-scale agent-based simulation of the Anasazi. Agents in this game use a cultural algorithm framework to modify their finite-state automata (FSA) controllers following the work of Fogel (1966). In the game, there can be two kinds of active agents: scripted and unscripted. Unscripted agents attempt to maximize their survivability, whereas scripted agents can be used to test the impact that various pure and compound strategies for cooperation and defection have on the social structures produced by the overall system. The goal of our experiments here is to determine the extent to which cooperation and competition need to be present among the agent households in order to produce a population structure and spatial distribution similar to what has been observed archaeologically. We do this by embedding a "trust in networks" game within the simulation. In this game, agents can choose from three pure strategies: defect, trust, and inspect. This game does not have a pure Nash equilibrium but instead has a mixed strategy Nash equilibrium such that a certain proportion of the population uses each at every time step, where the proportion relates to the quality of the signal used by the inspectors to predict defection. We use the cultural algorithm to help us determine what the mix of strategies might have been like in the prehistoric population. The simulation results indeed suggest a mixed strategy consisting of defectors, inspectors, and trustors was necessary to produce results compatible with the archaeological data. It is suggested that the presence of defectors derives from the unreliability of the signal which increases under drought conditions and produced increased stress on Anasazi communities and may have contributed to their departure.
    Full-text · Article · Jan 2006 · IEEE Transactions on Evolutionary Computation
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    • "We then wish to observe the social structures that emerge from the interaction of the agents and their environment. We began by looking at the tradeoffs between the tendencies for social aggregation on the one hand and the environmental constraints that tend to force dispersal on the other (Kobti et al., 2003). In the simulation, the agents effectively tried to strike a " balance " or " find a centering " between the social forces for aggregation and the environmental forces in the region. "
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    ABSTRACT: The initial version of the model used in this study, Village 1.0, was implemented by Tim Kohler and a team of developers mostly from Washington State University. The original model addressed environmental constraints only and did not attempt to model social interaction. In a recent paper we employed Cultural Algorithms as a framework in which to add selected social considerations. In this paper we extend our previous model by adding the ability of agents to perform symmetrically initiated or asymmetrically initiated generalized reciprocal exchange. We have developed a state model for agents' knowledge and, given agents' different responses based on this knowledge. Experiments have shown that the network structure of the systems without reciprocity was the simplest but least resilient. As we allowed agents more opportunities to exchange resources we produced more complex network structures, larger populations, and more resilient systems. Furthermore, allowing the agents to buffer their requests by using a finite state model improved the relative resilience of these larger systems. Introducing reciprocity that can be triggered by both requestors and donors produced the largest number of successful donations. This represents the synergy produced by using the information from two complementary situations within the network. Thus, the network has more information with which it can work and tended to be more resilient than otherwise.
    Full-text · Article · Oct 2003 · Computational and Mathematical Organization Theory
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    • "Agents, represented as households, reside in cells across the region. In previous work (Kobti, Reynolds, 2003, 2004) households were able to exchange their resources within a limited distance. Figure 3 illustrates the coverage area a household can access to exchange its resources. "
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    ABSTRACT: In this paper we take a multi-agent model of agricultural subsistence in the Mesa Verde region between 600 A.D. and 1300 A.D. and allow the emergence of a set of overlaid social networks over time in response to environmental dynamics. These overlaid networks include kinship, economic, and community level (hub) networks. Agents are able to participate in each of these networks and strategies for participation are learned using a framework for Cultural Evolution, Cultural Algorithms. Agents are embedded in the Mesa Verde environment. The environment is divided into cells. Each cell of the model contains a modelled agricultural, animal, hydrologic, forest and shrub components. The value for each of these components is derived from paleo-productivity and archaeological data from the region. The values can change over time as a result of migrations, changes in available water etc. These changes are dynamically programmed into the model. It is sho wn that changes in the environment can differentially affect the various layers and effects can ripple through to other networks. Thus, certain networks may be less resilient to environmental fluctuations than others and require additional maintenance from the population in order to maintain them. The extent to which the social system is able to learn strategies to adjust the network in response to environmental stress will be discussed. The results of the model are then compared to the known distribution and content of archaeological sites found in the regions.
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