Analysis of chemical signals in red fire ants by gas chromatography and pattern recognition techniques

Gas chromatographic (GC) profiles of cuticular hydrocarbon extracts obtained from individual and pooled ant samples were analyzed using pattern recognition techniques. Clustering according to the biological variables of social caste and colony were observed. Pooling individual extracts enhanced the recognition of patterns in the GC profile data characteristic of colony. Evidently, the contribution of the ant's individual pattern to the overall hydrocarbon profile pattern can obscure information about colony in the GC traces of cuticular hydrocarbon extracts obtained from red fire ants. Re-analysis of temporal caste and time period data on the cuticular hydrocarbon patterns demonstrates that sampling time and social caste must be taken into account to avoid unnecessary variability and possible confounding. This and the fact that foragers could not be separated from reserves and brood-tenders in all five laboratory colonies studied suggests that cuticular hydrocarbons as a class of sociochemicals cannot model every facet of nestmate recognition in Solenopsis invicta which in turn suggests a potential role for other compounds in the discrimination of alien conspecifics from nestmates.     

Geometric composite indicators with compromise Benefit-of-the-Doubt weights

This paper builds on Van Puyenbroeck and Rogge's (2017) ‘indirect’ multiplicative Benefit-of-the-Doubt (BoD) index number framework, in which the linear, data-driven BoD-model is used to estimate the importance of various sub-indicators within a geometric composite index (CI). We present an integrated framework that combines optimistic and pessimistic BoD-based weighting that enables to (1) establish the degree of unbalance in countries’ policy portfolio mix, (2) identify multiple underlying factors to explain inter-temporal evolution, and (3) explain for differences in country policy performances under the different weighting schemes following a multiplicative Bortkiewicz decomposition. In doing so, we use alternative optimistic and pessimistic BoD-models as existing models suffer from potential drawbacks in the identification of a country's comparative strengths and weaknesses. We illustrate our results with social inclusion data for the EU-countries for the period 2008-2013.     

Cultural dissemination in a complex network

In this paper, a complex contact network is constructed as substrate for cultural diffusion. Agents are partitioned into “clusters”, interpreted as sub-cultural groups. Cultural dissemination works both within the cluster and across clusters. To reflect connection intensity, an extra-cluster interaction damping coefficient is defined. The probability of interaction between agents through the intra-cluster contact is higher than through extra-cluster. Dynamical behavior of the cultural diffusion model is studied in this contact network. It is found that there is a critical value of extra-interaction intensity that separates the system from a multicultural to mono-cultural state for low values of the number of vectors (options) per cultural feature (attribute).     

Does observation of others affect learning in strategic environments? An experimental study

This paper presents experimental results from an analysis of two similar games, the repeated ultimatum game and the repeated best-shot game. The experiment examines whether the amount and content of information given to players affects the evolution of play in the two games. In one experimental treatment, subjects in both games observe not only their own actions and payoffs, but also those of one randomly chosen pair of players in the just-completed round of play. In the other treatment, subjects in both games observe only their own actions and payoffs. We present evidence suggesting that observation of other players' actions and payoffs may affect the evolution of play relative to the case of no observation. Received February 1996/Final version April 1998     

A social communication model based on simplicial complexes

Networks offer a powerful language with which to describe and study pairwise interaction. However, in many contexts, these rich collective phenomena require a higher-order approach to encode dynamical processes — for example in idea integration and information transmission (co-publication is a particularly familiar example). Here we introduce a novel framework for social communication by reshaping the networked system to be a simplicial complex, where the communication involves the interaction not only of individual nodes but also among cliques to which they belong. Simplicial complexes extend the network-based pairwise relationship to multiagent interaction. Assuming that the same individual in different cliques may play different roles, a threshold is designed and combined with the node state to determine the clique state. We employ the discrete microscopic Markov chain approach to model the simplex-based social communication and then obtain the underlying critical condition for information outbreaks. Moreover, we perform extensive numerical analysis of the proposed simplicial complex-based communication model and compare its performance with Monte Carlo simulation.     

Diffusion dynamics in small-world networks with heterogeneous consumers

Diffusions of new products and technologies through social networks can be formalized as spreading of infectious diseases. However, while epidemiological models describe infection in terms of transmissibility, we propose a diffusion model that explicitly includes consumer decision-making affected by social influences and word-of-mouth processes. In our agent-based model consumers’ probability of adoption depends on the external marketing effort and on the internal influence that each consumer perceives in his/her personal networks. Maintaining a given marketing effort and assuming its effect on the probability of adoption as linear, we can study how social processes affect diffusion dynamics and how the speed of the diffusion depends on the network structure and on consumer heterogeneity. First, we show that the speed of diffusion changes with the degree of randomness in the network. In markets with high social influence and in which consumers have a sufficiently large local network, the speed is low in regular networks, it increases in small-world networks and, contrarily to what epidemic models suggest, it becomes very low again in random networks. Second, we show that heterogeneity helps the diffusion. Ceteris paribus and varying the degree of heterogeneity in the population of agents simulation results show that the more heterogeneous the population, the faster the speed of the diffusion. These results can contribute to the development of marketing strategies for the launch and the dissemination of new products and technologies, especially in turbulent and fashionable markets. This paper won the best student paper award at the North American Association for Computational Social and Organizational Science (NAACSOS) Conference 2005, University of Notre Dame, South Bend, Indiana, USA. Preceding versions of this paper have been presented to the Conference of the North American Association for Computational Social and Organizational Science (NAACSOS), 2005, University of Notre Dame, South Bend, USA and to the Conference of the European Social Simulation Association (ESSA), 2005, Koblenz, Germany. Sebastiano Alessio Delre received his Master Degree in Communication Science at the University of Salerno. After one year collaboration at the Institute of Science and Technologies of Cognition (ISTC, Rome, Italy), now he is a PhD student at the faculty of economics, University of Groningen, the Netherlands. His work focus on how different network structures affect market dynamics. His current application domain concerns Agent-Based Simulation Models for social and economic phenomena like innovation diffusion, fashions and turbulent market. Wander Jager is an associate professor of marketing at the University of Groningen. He studied social psychology and obtained his PhD in the behavioral and social sciences, based on a dissertation about the computer modeling of consumer behaviors in situations of common resource use. His present research is about consumer decision making, innovation diffusion, market dynamics, crowd behavior, stock-market dynamics and opinion dynamics. In his work he combines methods of computer simulation and empirical surveys. He is involved in the management committee of the European Social Simulation Association (ESSA). Marco Janssen is an assistant professor in the School of Human Evolution and Social Change and in the Department of Computer Science and Engineering at Arizona State University. He got his degrees in Operations Research and Applied Mathematics. During the last 15 years, he uses computational tools to study social phenomena, especially human-environmental interactions. His present research focuses on diffusion dynamics, institutional innovation and robustness of social-ecological systems. He combined computational studies with laboratory and field experiments, case study analysis and archeological data. He is an associate editor-in-chief of the journal Ecology and Society.     

Relational dominant strategy equilibrium as a generalization of dominant strategy equilibrium in terms of a social psychological aspect of decision making

In this paper, incorporating a social psychological aspect of decision making, called attitudes, into analysis of games in normal form, the author proposes a new equilibrium concept, called relational dominant strategy equilibrium (RDSE). The author also analyzes relationships between RDSE and dominant strategy equilibrium (DSE), and shows the following fact: RDSE coincides with DSE under a condition on attitudes of players. The story of “The Gift of the Magi” by Henry is analyzed and given a convincing interpretation using the proposed equilibrium concept.     

Where do we stand on econophysics?

This issue contains papers selected from the contributions presented at the 5th International Conference on “Applications of Physics in Financial Analysis” (APFA5) held in Torino from June 29th to July 1st, 2006 (http://www.polito.it/apfa5). The issue collects recent applications of models and methods of statistical physics to economic problems. This interdisciplinary field of research, known as Econophysics, has seen intensive growth over the last decade. The challenge for econophysicists will be to go beyond the traditional views of economics and physics unifying the separate lines of development followed by the two disciplines over great part of the 20th century.“The conventional view serves to protect us from the painful job of thinking”, John Kenneth Galbraith (1908-2006).     

Model of prison riots

We present a model of a prison with two types of inmates. One (recidivists) is a better organized and has more influence on the formation of opinions, whereas the second one is more susceptible to the influence of internal and external pressure. We study, via computer simulations, the interplay between well-organized minority and the rest and how the final decision, like e.g. starting a riot, depends on such factors as: fraction of recidivists, their initial support of the riot and possibility of contacts among cells. We find that, as expected, the riot is more likely to start if there is more recidivists favoring it at the beginning. The influence of external factors (media) turned out to have a larger impact on the second group of prisoners. Contrary to a common practice, we show that in order to prevent riots it might be better not to block the inter-cell contacts.     

Ising,Schelling and self-organising segregation

The similarities between phase separation in physics and residential segregation by preference in the Schelling model of 1971 are reviewed. Also, new computer simulations of asymmetric interactions different from the usual Ising model are presented, showing spontaneous magnetisation (=self-organising segregation) and in one case a sharp phase transition.