# Economics  (E) Session 6

## Chair: Dexter Drupsteen

 491 Agent Based Model Exploration and Calibration using Machine Learning Surrogates [abstract] Abstract: Bringing Agent-Based Models closer to the data is an open challenge. While facilitating the comparison to more standard approaches, getting closer to the data promotes Agent-Based Models as a methodology. In this paper, we treat parameter space exploration from the machine learning problem setting of supervised learning and introduce machine learning surrogates as a fast and efficient means to explore positive calibrations from the parameter space. Three steps are involved: adaptively sampling a small number of simulations from the Agent-Based Model through the "active" learning problem setting, measuring the calibration quality of parameter combinations to real data with a chosen statistical hypothesis test, learn a powerful machine learning surrogate or "meta-model" on these "training" or modeling samples and rapidly filtering positive calibrations out of the parameter space for evaluation. Dramatic time savings are demonstrated by replacing the expensive Agent-Based Model and the machine learning surrogate. Though surrogates can potentially replace the agent-based model, we approach the simpler objective of filtering positive calibrations. Our aim is to provide a fast and efficient tool to explore the parameter space, while enabling policy-makers to evaluate and choose the particular parameterizations of interest. Finally, parameterizations of interest can be directly studied via the agent-based model. Ultimately, we do not wish to replace the agent-based model, but to help accelerate the turn-around time from real data to agent-based model calibrations that respect economic intuition and convey economic insight. We illustrate our approach by filtering positive calibrations (using the standard Kolmogorov-Smirnov two-sample test against the daily Standard and Poor's 500 Index) for the simple agent-based asset pricing model (introduced in "Heterogeneous beliefs and routes to chaos in a simple asset pricing model" by Brock and Holmes 1998) over ten parameters with generous ranges. Close Francesco Lamperti, Antoine Mandel, Andrea Roventini and Amir Sani 558 The Echoes of Bandwagon Through a Complex System of Innovation and Development [abstract] Abstract: Dating back from Schumpeter, literature on Innovation has evolved to the point of leading it’s object of study to the status of one of the main forces driving economic growth and development . The fact that Sollow's TFP black box is not so black anymore has probably something to do with understanding how the engine of innovation is greased. In this paper, we investigate if one of the cogwheels of this engine might be the bandwagon behaviour of consumers and its impact on the firm’s decision to engage on a certain type of innovative process. In order to do so, we introduce a new framework for complex agent-based models that is different from the commonly used Small Worlds Network, which we call Spatial Dynamic Awareness Model. Consumers have heterogeneous stochastic thresholds in respect to what we call “profile” towards new products and follow the distribution proposed by Moore (2005) as a baseline. They also have spatial mobility and bounded rationality (awareness), acquiring information and interacting only with agents inside their awareness radius to evaluate how many others are using a given product or technology and to ultimately decide to change their product of choice or not at each point in time. Firms on the other hand cannot see individual preferences, but analyses market saturation and concentration to decide on the amount of R&D investment and between process and product innovation. Simulations suggests that a society with a greater amount of crazy for technology individuals yields a faster saturation and de-concentration of the relevant market, generating more product than process innovations, higher mean prices and profits. We hope to reward the attendants of our presentation with new insights on network modelling and the importance of behavioural economics in better understanding the micro – macro process of innovation and economic development. Close João Basilio Pereima and Pedro Einloft 233 Emergence of social networks due to human mobility [abstract] Abstract: There is a recent burst of work on human mobility and social networks. However, the connection between these two important fields is still in its infancy or lack thereof. It is clear that both are closely related: People tend to visit popular places in a city with some frequency meeting other people there. If this occurs often, there is a chance of a friendship or acquaintance to emerge, linking people together. On the other hand, once you have established a social network, people tend to go together to the same places. In this way, there is feedback between human mobility in space and the structure of the social network. Mobility generates friends, and friends move together. We model the above situation with random walkers that visit places in space following a strategy akin to Lévy flights. We measure the encounters or coincidences in space and time and establish a link between walkers after they coincide several times. This generates a temporal network that is characterized by global quantities. We compare this dynamics with real data for two big cities: New York City and Tokyo. We use data from the location-based social network Foursquare and obtain the emergent temporal encounter network for New York City and Tokyo that we analyze in detail and compare with our model. Even though there are differences for the two cities, there are some common features: for instance, a long-range (Lévy-like) distribution of distances that characterize the emergent social network due to mobility in cities. This study contributes to the unification of two important fields: social networks and human mobility. Applications and implications to several fields like epidemics, social influence, voting, contagion models, behavioral adoption and diffusion of ideas will be discussed. Close Jose L. Mateos and Alejandro P. Riascos 118 Using statistical symmetries to characterize binary time series of the foreign exchange market [abstract] Abstract: We use the concept of statistical symmetry as the invariance of a probability distribution under transformation to analyze the sign dynamics of price difference in the foreign exchange market. Using a local hypothesis test with a stationary Markov process as model, we characterize different intervals of the sign time series of price difference as symmetric or not for the symmetries of independence and space odd reversion. For the test, we derive the probability of a binary Markov process to generate a given set of number of symbol pairs. As a particular result, we find that the foreign exchange market is essentially space odd reversible - interpreted as time reversible - but this symmetry is broken when there is a strong external influence. We also obtain that above a resolution of 90s the intervals of the sign time series are considered to be statistically symmetric implying that the direction of price movements in the market can be described by an independent random process. Close Arthur Matsuo Yamashita Rios de Sousa, Hideki Takayasu and Misako Takayasu 218 Analysis, prediction and control of technological progress [abstract] Abstract: Technological evolution is one of the main drivers of social and economic change, with transformative effects on most aspects of human life. How do technologies evolve? How can we predict and influence technological progress? To answer these questions, we looked at the historical records of the performance of multiple technologies. We first evaluate simple predictions based on a generalised version of Moore’s law. All technologies have a unit cost decreasing exponentially, but at a technology-specific rate. We then look at a more explanatory theory which posits that experience, measured as cumulative production, drives technological progress. These experience curves work relatively well in terms of forecasting, but in reality technological progress is a very complex process. To clarify the role of different causal mechanisms, we also study military production during World War II, where it can be argued that demand and other factors were exogenous. Finally, we analyse how to best allocate investment between competing technologies. A decision maker faces a trade-off between specialisation and diversification which is influenced by technology characteristics, risk aversion, demand and the planning horizon. Our methods are used to provide distributional forecasts for the cost of photovoltaic modules at different horizon, making it possible to evaluate their potential to provide an inexpensive source of energy in a relatively short horizon. Close Francois Lafond 373 Portfolio Optimization under Expected Shortfall: Contour Maps of Estimation Error [abstract] Abstract: The contour maps of the error of historical estimates for large random portfolios optimized under the Expected Shortfall (ES) risk measure are constructed. Similar maps for the sensitivity of the portfolio weights to small changes in the returns are also presented. The contour maps allow one to quantitatively determine the sample size (the length of the time series) required by the optimization for a given number of different assets in the portfolio, at a given confidence level and a given level of relative estimation error. The necessary sample sizes turn out to be unrealistically large for reasonable choices of the number of assets and the confidence level. These results are obtained via analytical calculations based on methods borrowed from the statistical physics of random systems, supported by numerical simulations. Close Fabio Caccioli, Imre Kondor and Gábor Papp

# Cognition  (C) Session 3

## Chair: Vincent Traag

 582 Inventors' Explorations and Performance Across Technology Space [abstract] Abstract: Technology is a complex system that evolves through the collective efforts of individual inventors. Understanding inventors' behaviors may thus enable predicting invention or improving technology policy. We examined data from 2.8 million inventors' 4 million patents and found most patents are created by explorers": inventors who move across different technology domains during their careers. Explorers are far more likely to enter technology domains that were highly related to their own individual inventive experience; this information enabled accurate prediction of individual explorers' future movements. Inventors who entered very related domains patented more there, but explorers who successfully entered moderately related domains were more likely to create high-impact patents. These findings may be instructive for inventors exploring the space of technologies, and useful for organizations or governments in forecasting or directing technological change. Close Jeff Alstott, Giorgio Triulzi, Bowen Yan and Jianxi Luo 72 Modeling the relation between income and commuting distance [abstract] Abstract: We discuss the distribution of commuting distances and its relation to income. Using data from Denmark, the UK, and the US, we show that the commuting distance is (i) broadly distributed with a slow decaying tail that can be fitted by a power law with exponent γ ≈ 3 and (ii) an average growing slowly as a power law with an exponent less than one that depends on the country considered. The classical theory for job search is based on the idea that workers evaluate the wage of potential jobs as they arrive sequentially through time, and extending this model with space, we obtain predictions that are strongly contradicted by our empirical findings. We propose an alternative model that is based on the idea that workers evaluate potential jobs based on a quality aspect and that workers search for jobs sequentially across space. We also assume that the density of potential jobs depends on the skills of the worker and decreases with the wage. The predicted distribution of commuting distances decays as 1/r^3 and is independent of the distribution of the quality of jobs. We find our alternative model to be in agreement with our data. This type of approach opens new perspectives for the modeling of mobility. Close Giulia Carra, Marc Barthelemy, Ismir Mulalic and Mogens Fosgerau 22 Experimental and theoretical approaches to collective estimation phenomena in human groups [abstract] Abstract: The well-known "Wisdom-of-Crowds" phenomenon, often mistakenly confused with collective intelligence, is not effective in every situation, especially under social influence. In simple estimation tasks, information sharing among group members may lead to strong biases in the collective estimate due to the reduction in diversity and independence of opinions. We are interested in finding conditions where social interactions could improve the accuracy of the collective estimate and its effectiveness. Specifying such conditions is an important step toward understanding how a human group can develop a form of collective intelligence emerging from social interactions between its members. We conduct a series of experiments aiming at understanding how a human group can use social information to converge toward the correct value in an estimation task. Subjects are sequentially asked to give a first guess, and then a second guess in the same estimation task after being provided with information about the average guess of the t previous subjects. We measure how this information affects the initial guesses of the subjects (with weight s) to various questions. We also measure the influence of "experts" (more knowledgeable subjects, introduced artificially with varying probability) and information lifetime (associated to t) on the convergence process. The distribution of social influence s is a Gaussian centered around s=2/3, with two additional very narrow peaks at 0 (highly confident subjects) and 1 ("followers"). We also find values of s below 0 or above 1, which correspond to subjects considered as "irrational" in micro-economic theories, and that may deeply affect the ability of a group to reach the right estimate. Unsurprisingly, the presence of experts improves both the final estimate and the speed of convergence. However, a decrease of the information lifetime t does not seem to influence the accuracy of the final estimate, but noticeably reduces the convergence time. Close Bertrand Jayles, Hye-Rin Kim, Ramon Escobedo, Stéphane Cezera, Adrien Blanchet, Tatsuya Kameda, Clément Sire and Guy Theraulaz 157 Privacy in Distributed Event Detection: an extended abstract [abstract] Abstract: We study the problem of event detection on distributed sensor networks. Prompt event detection is critical for many high-risk settings, for example evacuation following an earthquake. Distributed sensor networks are well suited for this task as they offer advantages such as high reliability and broad coverage. Distributed sensor networks can be organized in a centralized or decentralized way, the former offers higher accuracy, the latter lower communication volume. We study how this tradeoff varies for different network organizations, when a privacy cost is associated with communication. We assume that sensors pay a privacy cost for transmitting measurements. A real world example where this assumptions hold is earthquake detection with smartphones: If a device had to communicate regularly, the receiver could track its position throughout the day. We compare a centralized and a decentralized organization. In the centralized setting all sensors have to send their readings to the central event detection algorithm. In the decentralized setting the algorithm runs locally on a sensor, which alarms the central unit only if detects an event. This setting reduces the communication volume at the expense of accuracy. We propose a distributed protocol that reduces the privacy cost by reducing the communication to the central unit. Reducing communication is by itself desirable whenever remote communication is costly, for example low-power transmitters, and whenever computation is costly, for example if the central unit is a human supervisor with a limited attention span. The protocol allows sensors to ask their neighbors for an opinion on their measurements before reporting an event. The number of neighbors drives the accuracy/communication tradeoff. We test this protocol on different network topologies. We evaluate the system on detection accuracy and privacy cost. We expect to find a range of parameters for which a decentralized organization outperforms a centralized organization. Close Stefano Bennati, Catholijn Jonker and Chris Rouly 129 The streets all looked so strange: looking up digital imprints of immigrants’ spatial integration in cities [abstract] Abstract: People are constantly moving within cities and countries, facing the fact of the integration in habits and laws of new local cultures. Immigration phenomena have been studied and described so far by census data, which are indeed expensive to take, both in term of cost and time. Here we introduce a new methodology to explore the spatial integration of international immigrant communities in cities, exploring how Twitter users’ language might be a direct connection to their hometown and/or their nationality. We collect Twitter geo-localised data from 2012 to 2015 over a set of 58 out of the most populated cities in the world. We filter the users supposed to be residents in each city and their supposed-to-be place of residency. Finally, we assign to each user its most likely language. We conduct an extensive analysis on users’ spatial distribution within urban areas through a modified entropy metric, as a quantitative measure of the spatial integration of each language in the city. Results allowed us to characterized cities by their "Power of Integration”, as an attitude of hosting immigrant communities in urban areas, and by the corresponding process of integration of languages into different cultures, which is a quantitative measure of the differences between welcoming and hosting people in urban areas. Our findings provide a new way to detect the patterns of historically permanent immigration of people in urban areas, going beyond the estimation of past, current and foreshadowed global flows, towards a better comprehension of spatial integration phenomena on a city scale. Close Fabio Lamanna, Maxime Lenormand, María-Henar Salas-Olmedo, Gustavo Romanillos, Bruno Gonçalves and José Javier Ramasco

# Biology & Physics  (BP) Session 1

## Chair: Aleksandra Aloric

 272 Network theoretic constraints on metabolic diversity explain universal features of life on Earth [abstract] Abstract: All known life on Earth shares a set of common core reactions, used to synthesize and sustain every living individual. The network structure of these core reactions, and the corresponding peripheral reactions, have been analyzed in organisms in all three domains of life. These analyses have revealed similarities in the organization of their chemical reaction networks, which are quantified by topological measures such as diameter, degree distribution, and hierarchical modularity. We expand on this work with the analysis of an additional 21,000 bacterial genomes, 800 archaeal genomes, tens of metagenomes, and all documented biologically catalyzed reactions. We show that networks constructed from communities of individuals are distinguishable from individual organismal networks using some measures, but indistinguishable using others. Additionally, we show that real, coevolved metabolic communities are distinct from synthetic metabolic communities, which are constructed from randomly assembling individual organisms that have not jointly evolved. We find that regardless of organizational scale and whether or not communities are jointly evolved, these biological networks have heterogeneous degree distributions, which are associated with robustness to random mutation. Finally, we construct artificial networks that are topologically identical to individual metabolic networks, but differ in the distribution of chemical pathways relative to their topology. We show that in contrast to the real and synthetic communal networks, communities of these artificial networks do not exhibit scale-invariant properties. Interpreted in a network theoretic sense, this implies that networks which can sum together and maintain certain scale-invariant features must have highly constrained subgraphs. In the context of biological systems, these results suggest that the robustness of a communal metabolic network is highly sensitive to the particular chemical pathways present within individuals that constitute the community, and thus that a robust biosphere requires all its organisms to share a common core biochemistry. Close Harrison Smith, Hyunju Kim, Jason Raymond and Sara Imari Walker 419 Sampling the movement phenospace: Local linear models and the behavior of C. elegans [abstract] Abstract: The complexity of emergent systems can arise both from an intricate interplay of interacting parts and from the dynamical patterns performed by the system as a whole. But how do we find the dominant collective modes and how do we capture the dynamics of these modes with models amenable to analysis? Here we address these questions in the living movement of the nematode C. elegans. We apply a low-dimensional yet complete "eigenworm" representation of body shape to construct a principled parameterization of 2D postural movements. We use this representation to systematically explore the space of behavior by means of a local linear model and we develop a novel algorithm in which temporal locality is provided by the system itself by adaptively selecting the window of the local approximation. We apply our procedure to an example in which a heat shock is briefly administered to the worm’s head and we find a fine-scale description of the worm behavior which is remarkably more structured than previous, coarse-grained characterizations. We believe that our approach will be useful in dissecting other complex systems into more interpretable behaviors. Close Antonio Carlos Costa and Greg Stephens 465 Traveling chimera states in networks of hierarchically coupled Lattice Limit Cycle oscillators [abstract] Abstract: We investigate the emergence of chimera states in hierarchically connected networks, in a system undergoing a Hopf bifurcation. We show that under specific conditions the chimera states (characterized by coexisting, alternating, coherent and incoherent domains), acquire nested mean phase velocity distribution and can be traveling. The single oscillator dynamics follows the Lattice Limit Cycle (LLC) model which describes a prey-predator cyclic scheme among three species, presents a fourth order nonlinearity and gives rise to a limit cycle via a Hopf bifurcation. If LLC oscillators are arranged on a ring network topology with nonlocal interactions, stationary multi-chimera states emerge when the system is far from the Hopf bifurcation[1]. Hierarchical coupling connectivity [2] is introduced to the network in such a way that each LLC oscillator is coupled to all elements belonging to a Cantor set arranged around the ring. We provide evidence that this coupling scheme causes alterations to the structure of the coherent and incoherent regions. As space-time plots show, the (in)coherent regions present nested structures which travel around the ring keeping their profiles statistically stable in time. By recording how the position (i.e. the node number) of the maximum concentration value periodically changes in time, we calculate the corresponding frequency via the Fourier transform. We find that the speed of this motion decreases with increasing coupling strength [1]. Complex nested chimera structures, when regarded from the viewpoint of population dynamics, exemplify the rich organization which arises in communities of nonlocally interacting populations due to correlations in the connectivity rules. [1] Hizanidis, J., Panagakou, E., Omelchenko, I., Schöll, E., Hövel, P., Provata, A., Phys. Rev. E, vol. 92, 012915 (2015). [2] Omelchenko, I., Provata, A., Hizanidis, J., Schöll, E., Hövel, P., Phys. Rev. E, vol 91, 022917 (2015). Close Johanne Hizanidis, Evangelia Panagakou, Iryna Omelchenko, Eckehard Shoell, Philipp Hoevel and Astero Provata 13 Predicting the self-assembly of colloidal nanoparticles: A computer game [abstract] Abstract: The ability of atomic, colloidal, and nanoparticles to self organize into highly ordered crystalline structures makes the prediction of crystal structures in these systems an important challenge for science. The question itself is deceivingly simple: assuming that the underlying interaction between constituent particles is known, which crystal structures are stable. In this talk, I will describe a Monte Carlo simulation method [1] combined with a triangular tesselation method [2] to describe the surface of arbitrarily shaped particles that can be employed to predict close-packed crystal structures in colloidal hard-particle systems. I will show that particle shape alone can give rise to a wide variety of crystal structures with unusual properties, e.g., photonic band gap structures or highly diffusive crystals, but combining the choice of particle shape with external fields, like confinement [5], or solvent effects [6] can enlarge the number of possible structures even more. [1] L. Filion, M. Marechal, B. van Oorschot, D. Pelt, F. Smallenburg, and M. Dijkstra, Physical Review Letters 103, 188302 (2009). [2] J. de Graaf, R. van Roij and M. Dijkstra, Physical Review Letters 107, 155501 (2011). [3] K. Miszta, J. de Graaf, G. Bertoni, D. Dorfs, R. Brescia, S. Marras, L. Ceseracciu, R. Cingolani, R. van Roij, M. Dijkstra and L. Manna, Nature Materials 10, 872-876 (2011). [4] A.P. Gantapara, J. de Graaf, R. van Roij, and M. Dijkstra, Physical Review Letters 111, 015501 (2013). [5] B. de Nijs, S. Dussi, F. Smallenburg, J.D. Meeldijk, D.J. Groenendijk, L. Filion, A. Imhof, A. van Blaaderen, and M. Dijkstra, Nature Materials 14, 56-60 (2015). [6] J.R. Edison, N. Tasios, S. Belli, R. Evans, R. van Roij, and M. Dijkstra, Physical Review Letters 114, 038301 (2015) Close Marjolein Dijkstra 17 Residence time in a strip under jamming conditions [abstract] Abstract: The target of our study is to approximate numerically and, in some particular physically relevant cases, also analytically, the residence time of particles undergoing a biased motion on a two--dimensional vertical strip. The model is of some relevance to crowd dynamics, when high density of people at exits has to be prevented. The sources of asymmetry are twofold: (i) the choice of the boundary conditions (different reservoir levels) and (ii) the possible strong anisotropy from a drift nonlinear in density with prescribed directionality. The motion is modelled by the simple exclusion process on the square two-dimensional lattice. We focus on the effect on residence time due to jamming induced both by high reservoir levels at the strip exit end and by the presence of an impenetrable barrier placed at the middle of the strip. In both cases we find unexpected non-linear behavior of the residence time with respect to natural parameters of the model, such as the lateral movements probability and the width of the obstacle. We analyze our numerical results by means of two theoretical models, a Mean Field and a one-dimensional Birth and Death model. In most cases we find good agreement between theoretical predictions and numerical results. Close Emilio N.M. Cirillo, Rutger van Santen and Adrian Muntea

# Socio-Ecology  (S) Session 3

## Time and Date: 13:45 - 15:30 on 22nd Sep 2016

 404 Virus-like Dynamics for Modeling the Emergence of Defectors in the Spatial Public Goods Game [abstract] Abstract: In the last years, scientists coming from different communities investigated several socio-economic and biological phenomena under the lens of Evolutionary Game Theory (EGT). In general, studying the evolution of a population and identifying strategies that trigger cooperative behaviors constitute some of the major aims in this field. In particular, the emergence of cooperation becomes really interesting when agent interactions are based on games having a Nash equilibrium of defection, as in the Public Goods Game (PGG). The latter is analyzed by adding a viral spreading process based on the Susceptible-Infected-Susceptible (SIS) model. Notably, we consider a virus, with a spreading rate $\lambda$, whose effect is turning cooperators to defectors. In doing so, we can merge the two dynamics, i.e. the PGG and the epidemic spreading, in order to study the equilibria reached by the population. In particular, we analyze the relation between the spreading rate $\lambda$ (epidemic process) and the synergy factor (PGG). The proposed model aims to represent complex competitive processes, as the emergence of tumors. Notably, the latter, on a quality level, can be interpreted as the emergence of defection among the cells of an organism. Since some forms of tumors seem to be triggered by viruses, as the Papilloma Virus (PV), we deem that our investigations might shed some light on these complex phenomena, even if studied by a theoretical approach. Results of investigations can be of interest for those researchers interested in interdisciplinary applications of mathematical and physical models in biology, and for those interested in theoretical biology. To conclude, beyond to show results of our work we want to highlight the link between EGT and Biology. Close Marco Alberto Javarone and Nicoletta Schibeci Natoli Scialli 523 What is the role of human decisions in restoring a clear lake? – Analysing incremental complexity of agent-based models [abstract] Abstract: Human decisions affect and are affected by ecological systems in multiple ways. Natural resource modeling has commonly focused on decisions of resource users or strategic planners in one way. We argue that the dynamics of social-ecological systems (SES), however, emerge from multiple social-ecological interactions that are the result of decisions from different actors. We exemplify this with the case of lake restoration, i.e. the ecological regime shift from a turbid to a clear water state which is influenced by decisions from lake managers (governance) and individual households (beneficiaries + polluters). House owners can affect the nutrient inflow, the main driver for the lakes state, through their choices of sewage treatment. The management challenge, in this case, stems from the temporal and spatial decoupling between lake use activities by beneficiaries and the activities from distant actors eventually polluting the lake. Beneficiaries are those that enjoy ecosystem services such as drinking water, fish and recreation provided by the lake. We developed a coupled agent-based and system dynamics model to explore different pathways of managing the activities affecting the lake state back towards the clear state. Hereby, we discriminate between the timing of regulation measures (institutional level), pathways of rule enforcement (individual-institutional link), and the households initial attitude (individual level) in their effects on lake restoration time lags. By our incremental approach, we build a faceted understanding of how sensitive lake restoration is on the macro level to individual actor traits in the human-decision model on the micro level. Concluding, we reflect on the importance of the empirical as well as theoretical basis for human-decision modeling to increase its relevance for model-based learning. Close Romina Martin and Maja Schlüter 200 Reinforcement Learning in Social-Ecological System Models [abstract] Abstract: Recognizing the Earth System as a coupled complex social-ecological co-evolutionary system is important to enrich the discourse on global sustainability. However, it is an open question how to meaningfully formalize social dynamics in the context of mathematical social-ecological systems modeling. Existing models of social-ecological interactions often use a system dynamics approach of aggregated quantities, thereby not being able to account for complex social network effects, social stratification and inequalities - all presumably central issues for global sustainability; other types of models incorporate these ideas, but put their focus rather on regional, case specific social-ecological systems and tend not to use a "first-principle" approach. In this work we combine the concept of reinforcement learning (RL) with a co-evolutionary social-ecological systems perspective by providing the social agents with RL decision methods, making them capable of dealing with complex environments. Analytical calculations and computer simulations were performed to explore this scheme. It offers a promising view on a "first principle" method on agent behavior capable of dealing with unknown, possibly nonlinear environments to reveal potential counter intuitive traps and boundaries hindering social and ecological sustainability. Close Wolfram Barfuss, Jonathan F. Donges and Jürgen Kurths 165 Concepts behind the climate strategies. How C40 and its members define adaptation and mitigation? [abstract] Abstract: Networks within cities have become a feature in environmental governance, in particular in relation to dealing with climate change. Previous research has shown that the initiatives, such as C40, have created learning opportunities globally. Quantitative analyses have shown that connections have been formed and cities are learning from each other. However, less is known about what kinds of information is being shared through these networks. The concepts of adaptation and mitigation fundamentally advocate change. How they are conceptualised affects the way the climate change is addressed in practice. Previous research has shown that adaptation can be conceptualised as adjusting to the changing climate conditions (adjustment-based adaptation), as transforming the structures of society causing vulnerability (transformational adaptation), or as a combination of the two (reformist adaptation), and a similar classification of degree of change can also be found for mitigation. In this paper, our aim is to find out the degree of change as stated in the adaptation and mitigation strategies the C40 network and its members advocate. We approach the governance of urban adaptation as a complex system and ask how these concepts are defined in the documents produced by the C40 network and in the strategies of its member cities. We conduct an analysis of documents produced by C40 network and its member cities’ climate strategies with a computer assisted method to get the general overview of how far the documents support change. The result is controlled and deepened by close-reading of a representative sample of documents. Our findings reveal the concepts behind the climate strategies of C40 and its member cities that search to be the world leaders in addressing climate change. This gives context to the best practices promoted by the C40 network and its member cities and makes it possible to analyse them more profoundly. Close Milja Heikkinen and Sirkku Juhola 71 Opinion dynamics under out-group discrimination [abstract] Abstract: On many economic, political, social, and religious agendas, disagreement among individuals is pervasive. For example, the following are or have been highly debated: whether abortion, gay marriage, or death penalty should be legalized or not; the scientic standing of evolution; whether taxes/social subsidies/unemployment benefits/(lower bounds on) wages should be increased or decreased; the effectiveness of alternative (or standard') medicine such as homeopathy. In the field of so-called "opinion dynamics", long-run disagreement among individuals is sometimes considered a challenge, since a large class of models such as the famous model of DeGroot learning (DeGroot, 1974; Golub and Jackson, 2010) predict long-run opinion consensus as long as individuals form a connected group. However, there have recently been several models suggested which include a mode of anti-conformity' or `opposition' that predict disagreement even among connected interacting agents. Here, we present another such model of negative relationships among interacting agents, which extends the classical model of DeGroot for opinion dynamics. Our contributions are that we provide precise game-theoretic motivations of individuals' behavior as well as mathematically rigorous results on long-run disagreement in connected societies. Our game-theoretic motivation is that agents wish to coordinate with their friends (their 'in-group') and anti-coordinate with their enemies (their 'out-group'). Such behavior is well-documented in social psychology, both within the laboratory (see, e.g., Taifel 1978; Fehrler and Kosfeld, 2013) and outside. Our mathematical results include very general conditions for persistent disagreement among connected agents as well as an exhaustive graph-theoretical classification of long-run opinions in certain special cases. We find that persistent disagreement 'easily' obtains under the presence of negative relationships. As a consequence, crowd wisdom, the condition when all individuals learn the true state of nature or come close to it, is likely to fail. Close Steffen Eger