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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 15: | Linha 14: | ||
| Mertens and Lambin, 2000. land cover-change trajectories in southern cameroon. annals of the association of american geographers, 93, 467-494. | Mertens and Lambin, 2000. land cover-change trajectories in southern cameroon. annals of the association of american geographers, 93, 467-494. | ||
| (um modelo economico) | (um modelo economico) | ||
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| 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 318: | 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 337: | Linha 532: | ||
| ==== Pages ==== | ==== Pages ==== | ||
| - | CASA - Centre for Advanced Spatial Analysis (http://www.casa.ucl.ac.uk/news/index.htm). | ||
| - | |||
| + | Program for Evolutionary Dynamics (Harvard University) | ||
| ==== Authors ==== | ==== Authors ==== | ||
| - | ===Jaime Simão SICHMAN=== | ||
| - | Vale uma olhadela no site deste cara. | + | ===Samuel Bowles=== |
| - | E professor da USP Poli com interfaces com Portugal e Franca e no Brasil na area de | + | with **Suresh Naidu**: [[http://leg.ufpr.br/~pedro/papers/bowles_institutional_equilibrium.pdf|Institutional Equilibrium Selection by Intentional Idiosyncratic Play]], 2004 |
| - | Multi-agentes. | + | |
| - | http://www.pcs.usp.br/~jaime/#projetos | + | with **Hebert Gintis**: [[http://leg.ufpr.br/~pedro/papers/bowles_inheritance_of_inequality.pdf|The inheritance of inequality]], 2002 |
| - | + | ||
| - | ===Samuel Bowles=== | + | |
| - | with **Suresh Naidu**: Institutional Equilibrium Selection by Intentional Idiosyncratic Play, 2004 | + | |
| - | with **Hebert Gintis**: The inheritance of inequality, 2002 | + | === Portugali e Benenson=== |
| + | Segregação | ||
