Robustness of cultural communities in an open-ended Axelrod's model

We consider an open-ended set of cultural features in the Axelrod's model of cultural dissemination. By replacing the features in which a high degree of consensus is achieved by new ones, we address here an essential ingredient of societies: the evolution of topics as a result of social dynamics and debate. Our results show that, once cultural clusters have been formed, the introduction of new topics into the social debate has little effect on them, but it does have a significant influence on the cultural overlap. Along with the Monte-Carlo simulations, we derive and numerically solve an equation for the stationary cultural overlap based on a mean-field approach. Although the mean-field analysis reproduces qualitatively the characteristic phase transition of the Axelrod's model, it underestimates the cultural overlap, highlighting the role of the local interactions in the Axelrod's dynamics, as well as the correlations between the different cultural features.Comment: 6 pages and 5 figure

MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS

The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving goals and representing existing relations observed in real-world scenarios, and goal-based efficiency. Intelligent MABEL agents acquire spatial expressions and perform specific tasks demonstrating autonomy, environmental interactions, communication and cooperation, reactivity and proactivity, reasoning and learning capabilities. Their decisions maximize both task-specific marginal utility for their actions and joint, weighted marginal utility for their time-stepping. Agent behavior is achieved by personalizing a dynamic utility-based knowledge base through sequential GIS filtering, probability-distributed weighting, joint probability Bayesian correlational weighting, and goal-based distributional properties, applied to socio-economic and behavioral criteria. First-order logics, heuristics and appropriation of time-step sequences employed, provide a simulation-able environment, capable of re-generating space-time evolution of the agents.Environmental Economics and Policy,

The Borrower\u27s Tale: A History of Poor Debtors in \u3ci\u3eLochner\u3c/i\u3e Era New York City

This study adds to the recent scholarship on Progressivism in practice—fine-grained, place-based studies of reform at the local level—but focuses closely on the relationships among reformers, industry, and the law that an earlier generation of historians studied at the national level and outlined in broad brushstrokes. This study also builds upon the creditor-centered work of historians such as Mark H. Haller and John V. Alviti, but moves beyond their reliance upon distinctions and categories, such as those separating profit making credit providers from philanthropic credit providers, which were less important to borrowers than they have been for historians. In focusing primarily on the lived experience of poor borrowers, this article imports into the study of household credit relationships an approach mapped out by several historians of social welfare policy and institutions, who have attempted to reorient the institution-centered historiography of social welfare to give greater weight to the perspectives of welfare recipients. This study attempts to correct a similar imbalance in the historiography of household credit relationships. The value of viewing the history of credit through the lived experiences of working-class households is not solely in documenting the human dignity and agency of poor borrowers, although this is certainly one of the goals of this study. Rather, by looking at credit relationships from the borrower’s point of view, a number of different institutions, groups, and policies that borrowers experienced as simultaneous and overlapping, but that historians have usually studied separately from one another, are brought into the same analytic frame. Thus, in contrast to prior work, this study treats charitable and for-profit lenders to the poor together as participants in the same market for working-class credit. The debtors’ stories presented here show how impoverished families organized their financial lives, made ends meet, and employed borrowing as a survival strategy

Leadership in Small Societies

Multi-agent simulation was used to study several styles of leadership in small societies. Populations of 50 and100 agents inhabited a bounded landscape containing a fixed number of food sources. Agents moved about the landscape in search of food, mated, produced offspring, and died either of hunger or at a predetermined maximum age. Leadership models focused on the collection and redistribution of food. The simulations suggest that individual households were more effective at meeting their needs than a simple collection-redistribution scheme. Leadership affected the normative makeup of the population: altruistic leaders caused altruistic societies and demanding leaders caused aggressive societies. Specific leadership styles did not provide a clear advantage when two groups competed for the same resources. The simulation results are compared to ethnographic observations of leadership in Pacific island societies.Leadership, Reciprocity, Pacific Island Societies, Norms

Simple Heuristics in Complex Networks: Models of Social Influence

The concept of heuristic decision making is adapted to dynamic influence processes in social networks. We report results of a set of simulations, in which we systematically varied: a) the agents\' strategies for contacting fellow group members and integrating collected information, and (b) features of their social environment—the distribution of members\' status, and the degree of clustering in their network. As major outcome variables, we measured the speed with which the process settled, the distributions of agents\' final preferences, and the rate with which high-status members changed their initial preferences. The impact of the agents\' decision strategies on the dynamics and outcomes of the influence process depended on features of their social environment. This held in particular true when agents contacted all of the neighbors with whom they were connected. When agents focused on high-status members and did not contact low-status neighbors, the process typically settled more quickly, yielded larger majority factions and fewer preference changes. A case study exemplifies the empirical application of the model.Decision Making; Cognition; Heuristics; Small World Networks; Social Influence; Bounded Rationality

Identity and Democracy: Linking Individual and Social Reasoning

Following Amartya Sen\u27s approach, John Davis and Solange Regina Marin look at individual and social reasoning when examining the complex relationship between identity and democracy. They characterize democracy as a process of social or public reasoning that combines the individual reasoning of all citizens. Identity is explained in terms of personal identity, social identity, and individual identity. They argue that democracy in combining the individual reasoning of all citizens responds to individuals’ different personal identity concerns and needs, reflects their shared social identity interests and goals, and accords them rights and responsibilities associated with their many different individual identities

Adaptive build-up and breakdown of trust: An agent based computational approach

This article employs Agent-Based Computational Economics (ACE) to investigate whether, and under what conditions, trust is viable in markets. The emergence and breakdown of trust is modeled in a context of multiple buyers and suppliers. Agents develop trust in a partner as a function of observed loyalty. They select partners on the basis of their trust in the partner and potential profit, with adaptive weights. On the basis of realized profits, they adapt the weight they attach to trust relative to profitability, and their own trustworthiness, modeled as a threshold of defection. Trust and loyalty turn out to be viable under fairly general conditions.Agent-based computational economics;Inter-firm relations;Transaction costs;Governance;Trust;Complex adaptive systems