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| ==== Assuntos ==== | ==== Assuntos ==== | ||
| spatial equilibrium models | spatial equilibrium models | ||
| + | ricardian equivalence ("tax now" or "tax later") | ||
| ==== Papers==== | ==== Papers==== | ||
| - | |||
| - | Marietto, M., David, N., Sichman, J. and Coelho, H. 2003. Requirement analysis of agent-based simulation platforms: State of the art and new prospects. Lecture Notes in Artificial Intelligence:125-141. | ||
| Parker, D., Berger, T. and Manson, S., editors. 2002. Agent-based models of land-use and land-cover change. LUCC Report Series, 6, Indiana University. | Parker, D., Berger, T. and Manson, S., editors. 2002. Agent-based models of land-use and land-cover change. LUCC Report Series, 6, Indiana University. | ||
| Linha 16: | Linha 15: | ||
| (um modelo economico) | (um modelo economico) | ||
| + | |||
| + | |||
| + | ===Generating and Solving Imperfect Information Games=== | ||
| + | [[http://leg.ufpr.br/~pedro/papers/proceedings/koller_imperfect_information_95.pdf|D. Koller and A. Pfeffer]] | ||
| + | |||
| + | //Work on game playing in AI has typically ignored games of imperfect information such as poker. In | ||
| + | this paper, we present a framework for dealing with such games. We point out several important issues | ||
| + | that arise only in the context of imperfect information games, particularly the insufficiency of a | ||
| + | simple game tree model to represent the players’ information state and the need for randomization in | ||
| + | the players’ optimal strategies. We describe Gala, an implemented system that provides the user with a | ||
| + | very natural and expressive language for describing games. From a game description, Gala creates an | ||
| + | augmented game tree with information sets which can be used by various algorithms in order to find | ||
| + | optimal strategies for that game. In particular, Gala implements the first practical algorithm for finding | ||
| + | optimal randomized strategies in two-player imperfect information competitive games [Koller et al., | ||
| + | 1994]. The running time of this algorithm is polynomial in the size of the game tree, whereas previous | ||
| + | algorithms were exponential. We present experimental results showing that this algorithm is also | ||
| + | efficient in practice and can therefore form the basis for a game playing system.// | ||
| + | |||
| + | ===Evolution of cooperation: cooperation defeats defection in the cornfield model=== | ||
| + | [[http://leg.ufpr.br/~pedro/papers/jtb/koeslag_cornfield_model_03|J. H. Koeslag and E. Terblanche, 2003]] | ||
| + | |||
| + | //‘‘Cooperation’’ defines any behavior that enhances the fitness of a group (e.g. a community or species), but which, by its nature, can be exploited by selfish individuals, meaning, firstly, that selfish individuals derive an advantage from exploitation which is greater than the average advantage that accrues to unselfish individuals. Secondly, exploitation has no intrinsic fitness value except in the presence of the ‘‘cooperative behavior’’. The mathematics is described by the simple Prisoner’s Dilemma Game (PDG). It has previously been shown that koinophilia (the avoidance of sexual mates displaying unusual or atypical phenotypic features, such as mutations) stabilizes any inherited strategy in the simple or iterated PDG, meaning that it cannot be displaced by rare formsof alternative behavior which arise through mutation or occasional migration. In the present model equal numbersof cooperatorsand defectors(in the simple PDG) were randomly spread in a two-dimensional ‘‘cornfield’’ with uniformly distributed resources. Every individual was koinophilic, and interacted (sexually and in the PDG tournaments) only with individuals from within its immediate neighborhood. This model therefore tested whether cooperation can outcompete defection or selfishness in a straight, initially equally matched, evolutionary battle. The results show that in the absence of koinophilia cooperation was rapidly driven to extinction. With koinophilia there was a very rapid loss of cooperators in the first few generations, but thereafter cooperation slowly spread, ultimately eliminating defection completely. This result was critically dependent on sampling effects of neighborhoods. Small samples (resulting from low population densities or small neighborhood sizes) increase the probability that a chance neighborhood comes to consist predominantly of cooperators. A sexual preference for the most common phenotype in the neighborhood then makes that phenotype more common still. Once this occurs cooperation’s spread becomes almost inevitable.// | ||
| + | |||
| + | |||
| + | ===Social choice and electoral competition in the general spatial model=== | ||
| + | [[http://leg.ufpr.br/~pedro/papers/jet/banksa_electoral_competition_04.pdf|J. S. Banksa and J. Dugganb and M. Bretond, 2004]] | ||
| + | |||
| + | //This paper extends the theory of the core, the uncovered set, and the related undominated set to | ||
| + | a general set of alternatives and an arbitrary measure space of voters. We investigate the properties | ||
| + | of social preferences generated by simple games; we extend results on generic emptiness of the | ||
| + | core; we prove the general nonemptiness of the uncovered and undominated sets; and we prove the | ||
| + | upper hemicontinuity of these correspondences when the voters’ preferences are such that the core | ||
| + | is nonempty and externally stable. Finally, we give conditions under which the undominated set is | ||
| + | lower hemicontinuous.// | ||
| + | |||
| + | ===On Spatial Asymmetric Games=== | ||
| + | [[http://leg.ufpr.br/~pedro/papers/proceedings/ahmed_spatial_asymmetric_02.pdf|E. Ahmed and A. S. Hegazi and A. S. Elgazzar, 2002]] | ||
| + | |||
| + | //The stability of some spatial asymmetric games is discussed. Both | ||
| + | linear and nonlinear asymptotic stability of asymmetric hawk-dove | ||
| + | and prisoner’s dilemma are studied. Telegraph reaction diffusion equa- | ||
| + | tions for the asymmetric spatial games are presented. Asymmetric | ||
| + | game of parental investment is studied in the presence of both ordi- | ||
| + | nary and cross diffusions.// | ||
| + | |||
| + | ===The evolution of n-player cooperation-threshold games and ESS bifurcations=== | ||
| + | [[http://leg.ufpr.br/~pedro/papers/jtb/bach_cooperation_threshold_06.pdf|L. A. Bach and T. Helvik and F. B. Christiansen, 2006]] | ||
| + | |||
| + | //An evolutionary game of individuals cooperating to obtain a collective benefit is here modelled as an | ||
| + | n-player Prisioner's Dilemma game. With reference to biological situations, such as group foraging, we | ||
| + | introduce a threshold condition in the number of cooperators required to obtain the collective benefit. | ||
| + | In the simplest version, a three player game, complex behaviour appears as the replicator dynamics exhibits a | ||
| + | catastrophic event separating a parameter region allowing for cohexistence of cooperators and defectors and a | ||
| + | region of pure defection. Cooperation emerges through an ESS bifurcation, and cooperators only thrive beyond | ||
| + | a critical point in defecting populations. The results illustrate the qualitative difference between two | ||
| + | player games and multiple player games and thus the limitations to the generality of conclusions from two-player | ||
| + | games. We present a procedure to find the ESS in any n-player game with cost and benefit depending on the number | ||
| + | of cooperators. This was previously done by Motro in the special cases of convex and concave benefit functions and | ||
| + | constant cost.// | ||
| + | |||
| + | |||
| + | ===Spatial evolution of automata in the prisoners’ dilemma=== | ||
| + | [[http://leg.ufpr.br/~pedro/papers/jebo/kirchkamp_evolution_pd_00.pdf|O. Kirchkamp, 2000]] | ||
| + | |||
| + | //We apply the idea of evolution to a spatial model. Prisoners’ dilemmas or coordination games | ||
| + | are played repeatedly within neighbourhoods where players do not optimise but instead copy successful | ||
| + | strategies. Discriminative behaviour of players is introduced representing strategies as small | ||
| + | automata, which can be in different states against different neighbours. Extensive simulations show | ||
| + | that cooperation persists even in a stochastic environment, that players do not always coordinate | ||
| + | on risk dominant equilibria in 2x2 coordination games, and that success among surviving strategies | ||
| + | may differ. We present two analytical models that help understanding of these phenomena.// | ||
| + | |||
| + | ===The Adaptive Dynamics of Altruism in Spatially Heterogeneous Populations=== | ||
| + | [[http://leg.ufpr.br/~pedro/papers/ijoe/galliard_altruism_heterogeneous_06.pdf|J. Galliard and R. Ferriere and U. Dieckmann, 2003]] | ||
| + | |||
| + | //We study the spatial adaptive dynamics of a continuous trait that measures individual investment in altruism. | ||
| + | Our study is based on an ecological model of a spatially heterogeneous population from which we derive an appropriate | ||
| + | measure of fitness. The analysis of this fitness measure uncovers three different selective processes controlling the | ||
| + | evolution of altruism: the direct physiological cost, the indirect genetic benefits of cooperative interactions, and the | ||
| + | indirect genetic costs of competition for space. In our model, habitat structure and a continuous life cycle makes the | ||
| + | cost of competing for space with relatives negligible. Our study yields a classification of adaptive patterns of altruism according to the shape of the costs of altruism (with decelerating, linear, or accelerating dependence on the investment in altruism). The invasion of altruism occurs readily in species with accelerating costs, but large mutations are critical for altruism to evolve in selfish species with decelerating costs. Strict selfishness is maintained by natural selection only under very restricted conditions. In species with rapidly accelerating costs, adaptation leads to an evolutionarily stable rate of investment in altruism that decreases smoothly with the level of mobility. A rather different adaptive pattern emerges in species with slowly accelerating costs: high altruism evolves at low mobility, whereas a quasiselfish state is promoted in more mobile species. The high adaptive level of altruism can be predicted solely from habitat connectedness and physiological parameters that characterize the pattern of cost. We also show that environmental changes that cause increased mobility in those highly altruistic species can beget selection-driven self-extinction, which may contribute to the rarity of social species. // | ||
| ===Swarming methods for geospatial reasoning=== | ===Swarming methods for geospatial reasoning=== | ||
| Linha 56: | Linha 136: | ||
| ===The consequences of labour mobility for redistribution: tax vs. transfer competition=== | ===The consequences of labour mobility for redistribution: tax vs. transfer competition=== | ||
| - | [[http://leg.ufpr.br/~pedro/paper/jpe/hindriks_labour_mobility_99.pdf|J. Hindriks, 1999]] | + | [[http://leg.ufpr.br/~pedro/papers/jpe/hindriks_labour_mobility_99.pdf|J. Hindriks, 1999]] |
| //In a context where both the poor and the rich are (imperfectly) mobile, this paper | //In a context where both the poor and the rich are (imperfectly) mobile, this paper | ||
| Linha 173: | Linha 253: | ||
| if it is not series-parallel. More generally, Pareto inefficient equilibria occur in a network if and only if one | if it is not series-parallel. More generally, Pareto inefficient equilibria occur in a network if and only if one | ||
| of three simple networks is embedded in it.// | of three simple networks is embedded in it.// | ||
| - | |||
| - | ===A random matching theory=== | ||
| - | [[http://leg.ufpr.br/~pedro/papers/geb/aliprantis_random_matching_06.pdf|C.D. Aliprantis and G. Camera and D. Puzzellob, 2006]] | ||
| - | |||
| - | //We develop theoretical underpinnings of pairwise random matching processes. We formalize the mechanics | ||
| - | of matching, and study the links between properties of the different processes and trade frictions. | ||
| - | A particular emphasis is placed on providing a mapping between matching technologies and informational | ||
| - | constraints.// | ||
| ===Coordination and cooperation in local, random and small world networks: Experimental evidence=== | ===Coordination and cooperation in local, random and small world networks: Experimental evidence=== | ||
| Linha 231: | Linha 303: | ||
| + | ===Noncooperative Bargaining and Spatial Competition=== | ||
| + | H. Bester, 1989. | ||
| + | Econometrica | ||
| + | //The paper presents a bargaining approach to spatial competition. Sellers compete by | ||
| + | choosing locations in a market region. Consumers face a cost to moving from one | ||
| + | place to another. The price od the good is determined as the perfect equilibrium | ||
| + | of a bargaining game between seller and buyer. In this game, the consumer has the | ||
| + | outside option to move to another seller so that prices at all stores are | ||
| + | independent. Existence od a location-price equilibrium is established. The | ||
| + | outcome approaches the perfectly competitive one if the consumer's costs of | ||
| + | traveling become negligible or if the number of sellers tends to infinity.// | ||
| + | |||
| + | ===The Evolution of Cooperation in Heterogeneous Populations=== | ||
| + | S. Bowles and H. Gintis, 2003 | ||
| + | |||
| + | //How do human groups maintain a high level of cooperation despite a low | ||
| + | level of genetic relatedness among group members? We suggest that many | ||
| + | humans have a predisposition to punish those who violate group-beneficial | ||
| + | norms, even when this reduces their fitness relative to other group members. | ||
| + | Such altruistic punishment is widely observed to sustain high levels of cooperation | ||
| + | in behavioral experiments and in natural settings. It is known that if | ||
| + | group extinctions are sufficiently common, altruistic punishment may evolve | ||
| + | through the contribution of norm adherence to group survival. Additionally, | ||
| + | those engaging in punishment of norm violators may reap fitness benefits if | ||
| + | their punishment is treated as a costly signal of some underlying but unobservable | ||
| + | quality as a mate, coalition partner, or opponent. Here we explore a | ||
| + | different mechanism in which neither signaling nor group extinctions plays a | ||
| + | role. Rather, punishment takes the form of ostracism or shunning, and those | ||
| + | punished in this manner suffer fitness costs. | ||
| + | We offer a model of this behavior, which we call strong reciprocity: where | ||
| + | members of a group benefit from mutual adherence to a social norm, strong | ||
| + | reciprocators obey the norm and punish its violators, even though they receive | ||
| + | lower payoffs than other group members, such as selfish agents who violate | ||
| + | the norm and do not punish, and pure cooperators who adhere to the norm | ||
| + | but free-ride by never punishing. Our agent-based simulations show that, | ||
| + | under assumptions approximating some likely human environments over the | ||
| + | 100,000 years prior to the domestication of animals and plants, the proliferation | ||
| + | of strong reciprocators when initially rare is highly likely, and that | ||
| + | substantial frequencies of all three behavioral types can be sustained in a | ||
| + | population.// | ||
| + | |||
| + | |||
| + | ===Generous and Greedy Strategies=== | ||
| + | [[|B. Carlsson and S. Johansson, 1998]] | ||
| + | |||
| + | //We introduce generous, ecent-matched, and greedy strategies as concepts for | ||
| + | analyzing games. A two person prisioner's dilemma game is described by the | ||
| + | four outcomes (C,D), (C,C), (D,C) and (D,D). In a generous strategy the | ||
| + | proportion of (C,D) is larger than (D,C), i.e. the probability of facing | ||
| + | defect is larger than the probability of defecting, An event-matched strategy | ||
| + | has the (C,D) proportion approximately equal to that of (D,C). A greedy | ||
| + | strategy is an inverted generous atrategy. The basis of the partition is that | ||
| + | it is a zero-sum game given that the sum of the proportions of strategies (C,D) | ||
| + | must equal that of (D,C). In a population simulation, we compare the PD game | ||
| + | with the chicken game (CG), given complete as well as partial knowledge of the | ||
| + | rules for moves in the other strategies. In a traffic intersection example, we | ||
| + | expected a co-operating generous strategy to be successful when the cost for | ||
| + | mutual collision was high in addition to the presence of uncertainty. The | ||
| + | simulation indeed showed that a generous strategy was successful in the CG part, | ||
| + | in which agents faced uncertainty about the outcome. If the resulting zero-sum | ||
| + | game is changed from a PD game to a CG, of if the noise level is increased, the | ||
| + | sucessful strategies will favor a generous strategy rather an even-matched or | ||
| + | greedy strategy.// | ||
| + | |||
| + | ===Spatial and Density Effects in Evolutionary Game Theory=== | ||
| + | [[|R. Cressman and G. T. Vickers, 1996]] | ||
| + | |||
| + | //Two models are considered for the study of game dynamics in a spatial domain. | ||
| + | Both models are continuous in space and time and give rise to reaction-diffusion | ||
| + | equations. The spatial domain is homogeneous but the mobility of the individuals | ||
| + | is allowed to depend upon the strategy. The models are analysed for spatial | ||
| + | patterns (via a Turing instability) and also for the direction of the travelling | ||
| + | wave that replaces one strategy by another. It is shown that the qualitative | ||
| + | behaviour of the two models is quite different. When considering the existence | ||
| + | of spatial patterns and deciding whether increased mobility is helpful or not, | ||
| + | it is shown that the answers depend crucially upon the model equations. Since | ||
| + | both models (in the absence of spatial variation) are quite standard, it is clear | ||
| + | that considerable care has to be exercised in the formulation of spatial models | ||
| + | and in their interpretation.// | ||
| + | |||
| + | |||
| + | ===Modern Game Theory: Deduction vs. Induction=== | ||
| + | [[|A. Greenwald, 1997]] | ||
| + | |||
| + | The aim of this paper is twofold: firstly, to present a survey of the theory | ||
| + | of games, and secondly, to contrast deductive and inductive reasoning in game | ||
| + | theory. This report begins with an overview of the classical theory of | ||
| + | strategic form games of complete information. This theory is based on the | ||
| + | traditional economic assumption of rationality, common knowledge of which | ||
| + | yields Nash equilibrium as a deductive solution to games in this class. In the | ||
| + | second half of this paper, modern game-theoretic ideas are introduced. In | ||
| + | particular, learning and repeated games are analyzed using an inductive model, | ||
| + | in the absence of common knowledge. In general, inductive reasoning does not | ||
| + | gives rise to the Nash equilibrium when learning is deterministic, unless initial | ||
| + | beliefs are somehow fortuitously chosen. However, computer simulations show that | ||
| + | in the presence of a small random component, repeated play does indeed converge | ||
| + | to Nash equilibrium. This research is of interest to computer scientists | ||
| + | because modern game theory is a natural framework in which to formally study | ||
| + | multi-agent systems and distributed computing. | ||
| + | |||
| + | |||
| + | ===Self-organized Criticality in Spatial Evolutionary Game Theory=== | ||
| + | [[|T. Killingback and M. Doebeli, 1997]] | ||
| + | |||
| + | //Self-organized criticality is an important framework for understanding the | ||
| + | emergence of scale-free natural phenomena. Cellular automata provide simple | ||
| + | interesting models in which to study self-organized criticality. We consider the | ||
| + | dynamics of a new class of cellular automata which are constructed as natural | ||
| + | spatial extensions of evolutionary game theory. This construction yields a | ||
| + | discrete one-parameter family of cellular automata. We show that there is a range | ||
| + | of parameter values for which this system exhibits complex dynamics with long | ||
| + | range correlations between states in both time and space. In this region the | ||
| + | dynamics evolve to a self-organized critical state in which structures exist on | ||
| + | all time and length scales, and the relevant statistical measures have power | ||
| + | law behaviour.// | ||
| + | |||
| + | ===Concentration of Competing Retail Stores=== | ||
| + | [[|H. Konishi]] | ||
| + | |||
| + | //The geographical concentration of stores that sell similar commodities is | ||
| + | analyzed using a two-dimensional spatial competition model. A higher | ||
| + | concentration of stores attracts more consumers with taste uncertainty and low | ||
| + | price expectations (a market-size effect), while it leads to fiercer price | ||
| + | competition (a price-cutting effect). Our model is general enough to allow | ||
| + | for the coexistence of multiple (possibly) asymmetric clusters of stores. We | ||
| + | provide sufficient conditions for the nonemptiness of equilibrium store location | ||
| + | choices in pure strategies. Through numerical examples, we illustrate the | ||
| + | trade-off between the market-size and price-cutting effects, and provide | ||
| + | agglomeration patterns of stores in special cases.// | ||
| + | |||
| + | |||
| + | ===Discrete Time Spatial Models Arising in Genetics, Evolutionary Game Theory, and Branching Processes=== | ||
| + | [[|J. Radcliffe and L. Rass, 1996]] | ||
| + | |||
| + | //A saddle point method is used to obtain the speed of first spread of new | ||
| + | genotypes in genetic models and of new strategies in game theoretic models. It is | ||
| + | also used to obtain the speed of the forward tail of the distribution of farthest | ||
| + | spread for branching process models. The technique is applicable to a wide range | ||
| + | of models. They include multiple allele and sex-linked models in genetics, | ||
| + | multistrategy and bimatrix evolutionary games, and multitype and demographic | ||
| + | branching processes. The speed of propagation has been obtained for genetics | ||
| + | models (in simple cases only) by Weinberger [1, 2] and Lui [3-7], using exact | ||
| + | analytical methods. The exact results were obtained only for two-allele, | ||
| + | single-locus genetic models. The saddle point method agrees in these very | ||
| + | simple cases with the results obtained by using the exact analytic methods. | ||
| + | Of course, it can also be used in much more general situations far less tractable | ||
| + | to exact analysis. The connection between genetic and game theoretic models is | ||
| + | also briefly considered, as is the extent to which the exact analytic methods | ||
| + | yield results for simple models in game theory.// | ||
| + | |||
| + | ===Nash equilibrium in a spatial model of coalition bargaining=== | ||
| + | [[|N. Schofield and R. Parks]] | ||
| + | |||
| + | //In the model presented here, n parties choose policy positions in a space Z | ||
| + | of dimension at least two. Each party is represented by a "principal" whose true | ||
| + | policy preferences on Z are unknown to other principals. In the first version of | ||
| + | the model the party declarations determine the lottery outcome of coalition | ||
| + | negotiation. The coalition risk functions are common knowledge to the parties. | ||
| + | We assume these coalition probabilities are inversely proportional to the | ||
| + | variance of the declarations of the parties in each coalition. It is shown that | ||
| + | with this outcome function and with three parties there exists a stable, pure | ||
| + | strategy Nash equilibrium, z* for certain classes of policy preferences. This | ||
| + | Nash equilibrium represents the choice by each party principal of the position | ||
| + | of the party leader and thus the policy platform to declare to the electorate. | ||
| + | The equilibrium can be explicitly calculated in terms of the preferences of the | ||
| + | parties and the scheme of private benefits from coalition membership. In | ||
| + | particular, convergence in equilibrium party positions is shown to occur if the | ||
| + | principals' preferred policy points are close to colinear. Conversely, divergence | ||
| + | in equilibrium party positions occurs if the bliss points are close to | ||
| + | symmetric. If private benefits (the non-policy perquisites from coalition | ||
| + | membership) are sufficiently large (that is, of the order of policy benefits), | ||
| + | then the variance in equilibrium party positions is less than the variance in | ||
| + | ideal points. The general model attempts to incorporate party beliefs concerning | ||
| + | electoral responses to party declarations. Because of the continuity properties | ||
| + | imposed on both the coalition and electoral risk functions, there will exist | ||
| + | mixed strategy Nash equilibria. We suggest that the existence of stable, pure | ||
| + | strategy Nash equilibria in general political games of this type accounts for the | ||
| + | non-convergence of party platforms in multiparty electoral systems based on | ||
| + | proportional representation.// | ||
| + | |||
| + | |||
| + | ===Stability of Spatial Equilibrium=== | ||
| + | [[|T. Tabuchi and D. Zeng, 2001]] | ||
| + | |||
| + | //We consider interregional migration, where regions may be interpreted as clubs, | ||
| + | social subgroups, or strategies. Using the positive definite adaptive (PDA) | ||
| + | dynamics, which include the replicator dynamics, we examine the evolutionary | ||
| + | stable state (ESS) and the asymptotic stability of the spatial distribution of | ||
| + | economic activities in a multiregional system. We derive an exact condition | ||
| + | for the equivalence between ESS and asymptotically stable equilibrium in each | ||
| + | PDS dynamic. We show that market outcome yields the efficiency allocation of | ||
| + | population with an additional condition. We also show that interior equilibria | ||
| + | are stable in the presence of strong congestion diseconomies but unstable in the | ||
| + | presence of strong agglomeration economies with further condition.// | ||
| + | |||
| + | |||
| + | ===Spatial Games with Adaptive Tit-for-Tats=== | ||
| + | [[http://leg.ufpr.br/~pedro/papers/tzafestas00.pdf|E. S. Tzafestas, 2000]] | ||
| + | |||
| + | |||
| + | //This paper presents an adaptive tit-for-tat strategy and a study of its | ||
| + | behavior in spatial IPD games. The adaptive tit-for-tat strategy is shown | ||
| + | elsewhere to demonstrate high performance in IPD tournaments or individual | ||
| + | IPD games with other types of strategies, and obtains higher scores than the | ||
| + | pure tit-for-tat strategy. In spatial IPD games, the strategy exhibits stability and | ||
| + | resistance to perturbations, and those properties are more pronounced in | ||
| + | variations of the spatial game model that induce some degree of “noise” : | ||
| + | probabilistic winning, spatial irregularity and continuous time. The adaptive tit- | ||
| + | for-tat strategy is also compared to pure tit-for-tat and found to be more stable | ||
| + | and predominant in perturbed environments.// | ||
| ==== Journals ==== | ==== Journals ==== | ||
| Linha 249: | Linha 531: | ||
| Caípitulo 2 do Russel sobre agentes. | Caípitulo 2 do Russel sobre agentes. | ||
| - | ==== Authors ==== | + | ==== Pages ==== |
| - | ===Jaime Simão SICHMAN=== | + | Program for Evolutionary Dynamics (Harvard University) |
| - | Vale uma olhadela no site deste cara. | + | ==== Authors ==== |
| - | E professor da USP Poli com interfaces com Portugal e Franca e no Brasil na area de | + | |
| - | Multi-agentes. | + | |
| - | http://www.pcs.usp.br/~jaime/#projetos | ||
| ===Samuel Bowles=== | ===Samuel Bowles=== | ||
| - | with **Suresh Naidu**: Institutional Equilibrium Selection by Intentional Idiosyncratic Play, 2004 | + | with **Suresh Naidu**: [[http://leg.ufpr.br/~pedro/papers/bowles_institutional_equilibrium.pdf|Institutional Equilibrium Selection by Intentional Idiosyncratic Play]], 2004 |
| + | |||
| + | with **Hebert Gintis**: [[http://leg.ufpr.br/~pedro/papers/bowles_inheritance_of_inequality.pdf|The inheritance of inequality]], 2002 | ||
| - | with **Hebert Gintis**: The inheritance of inequality, 2002 | + | === Portugali e Benenson=== |
| + | Segregação | ||
