R. Axelrod. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press, 1997.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....follows: c. xi w(I) xi w(X) x c I O) il iK The core has the following membership function associated with it: Xc (x) v= w(I) x i) v = xi, w(K) 2) iI iK where: v = w(I) with the preference = as a weak order fuzzy relation with membership function v = R x R [0,1]. The expressions (1) and (2) correspond to the game theoretic model with fuzzy coalitions and contain only the terms relative to the fuzzy payments. For the purposes of this article the fuzzy core was changed to include the capacities of each agent and the tasks to fulfill defined by the demand, ....

....= fuzzy payoff per unit for car production. w(k l) fuzzy payoff per unit for Body Production. w(k 2 ) fuzzy payoff per unit for Motor Production. w(k 3 ) fuzzy payoff per unit for Transmission Production. w(k 4 ) fuzzy payoff per unit for car assembly. t = uniform random variable in [0,1]. The forecasting model for the demand is the following: 100 5t 5 t, for t=l, 5 and t is uniform in [0,1] 4) Two solution techniques were studied. First, the Excel solver was used. Next, genetic algorithms were used and Evolver software. Testbed implementation details and simulation results ....

[Article contains additional citation context not shown here]

Axelrod, R. (1997). The complexity of cooperation: agent based models of competition and collaboration. Princeton University Press.

....for some type of cooperation . And finally, can this cooperation benefit both individual and collective performances . Co evolution and competitive fitness are relevant to several artificial life environments such as Verve [1] PolyWorld [2] Tierra [3] and Bioland [4] Kauffman [5] and Axelrod [6] have made significant contributions to the analysis of coevolving systems in the context of self organization and the iterated prisoner s dilemma respectively. Binmore [7] provides a critical review on the problem of simulating evolution and cooperation based on the studies performed by Axelrod. ....

....Thus, a strategy would take the form of a decision rule that specifies the probability of cooperation or defection as a function of the history of the interaction so far. The PD problem defines a payoff matrix, similar to the score function shown in Fig. 2. Unlike the studies published by Axelrod [6], the artificial life model reported here does not implement a traditional iterated prisoner s dilemma system. In this paper, for example, some of the competing individuals cannot recognise a previous rival. Moreover, such type of organism is unable to remember prior moves outcomes. The design of ....

[Article contains additional citation context not shown here]

R. Axelrod, The complexity of cooperation: Agent-based models of competition and collaboration, Princeton University Press: Princeton, 1997.

....The trade off between exploring for better individuals (strategies, solutions to problems, etc. and the cost of exploration due to failure to exploit what is the currently known best is a common thread in many models that use evolutionary algorithms to modify populations (cf. Holland, 1994] [Axelrod, 1997]) In the model studied here, the amount of exploration done by the EA is controlled primarily by three parameters: 1) the mutation rate, mu rt , the probability that each gene in a new individual is mutated; 2) the mutation spread, mu sd , the standard of deviation of the mean 0 displacement ....

Axelrod, Robert. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. To be published by Princeton University Press in 1997.

....The trade off between exploring for better individuals (strategies, solutions to problems, etc. and the cost of exploration due to failure to exploit what is the currently known best is a common thread in many models that use evolutionary algorithms to modify populations (cf. Holland, 1994] [Axelrod, 1997]) In the model studied here, the amount of exploration done by the EA is controlled primarily by three parameters: 1) the mutation rate, mut, the probability that each gene in a new individual is mutated; 2) the mutation spread, musc, the standard of deviation of the mean 0 displacement added ....

Axelrod, Robert. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. To be published by Princeton University Press in 1997.

....lation and territoriality. Thu2 while still of the basis of rational choices, Axelrod neverthelessinclu2# the hu man factor in the game, taking into accou t huz n individu l and social characteristics. He goes a step fu ther in his suzzC#W2 t book The Com plexity of Cooperation ([2]) Francis Heylighen [45] douW; that reciprocal altru2z can su#W 5 tly accou nt for cooperative behavior in largegrou ps of individu als. In [46] he introdu#q another model for the evolu#zz of cooperation especially in hu man society. On the basis of memes, which we described earlier, ....

Robert Axelrod. The Complexity of Cooperation: Agent-based Model of Competition and Cooperation. Princeton University Press, 1997. 127

....no fear of reprisal in future interactions. It is more difficult to explain why we encounter cooperation in the real world examples of these social dilemmas. A few attempts have been made to attempt to explain, via computer simulations why cooperation can emerge and exist. Simulations by Axelrod[2] illustrate that norms of cooperation can be created and enforced. Axelrod created a model that allows players in the model to punish those that break the norm of cooperation. This punishment allows the emergence of cooperation but does not guarantee the stability of cooperation as a norm. A ....

Robert Axelrod. The Complexity of Cooperation : Agent-Based Models of Competition and Collaboration. Princeton Univ Pr, 1997.

....a definition based on three major aspects will be used. The first aspect is focused on emergent properties as a largescale effect of locally interacting agents: Emergent properties are often surprising because it can be hard to anticipate the full consequences of even simple forms of interaction (Axelrod, 1997). Jacques Ferber s view is more centralized on emergent organization: Even societies considered as being complex such as colonies of bees or ants, should not necessarily be considered as individuals in their own right if we wish to understand their organization and the regulation and evolution ....

Axelrod, R. (1997). The Complexity of Cooperation - Agent-Based Models of Competition and Collaboration. Princeton University Press. Princeton, New Jersey.

....over a fixed number of strategy types, and the strategies reproduce over time in direct proportion to their relative fitness. Exploiting the recent advent of more powerful computational tools, such as object oriented programming, ACE researchers such as Arifovic (1994) Arthur et al. 1997) Axelrod (1997), Epstein Axtell (1996) Kirman (1997) Kollman et al. 1997) Marks (1992) McFadzean and Tesfatsion (1999) Miller (1996) Tesfatsion (1997a,b) Vriend (1995) and Young (1998) have been able to extend this earlier work on evolutionary economics in four key ways. First, agents in ACE ....

Axelrod, Robert (1997), The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton: Princeton University Press.

....reputation, regulation and territoriality. Thus, while still of the basis of rational choices, Axelrod nevertheless includes the human factor in the game, taking into account human individual and social characteristics. He goes a step further in his subsequent book The Complexity of Cooperation ([2]) Francis Heylighen [45] doubts that reciprocal altruism can suciently account for cooperative behavior in large groups of individuals. In [46] he introduces another model for the evolution of cooperation especially in human society. On the basis of memes, which we described earlier, he ....

Robert Axelrod. The Complexity of Cooperation: Agent-based Model of Competition and Cooperation. Princeton University Press, 1997.

.... simulation technique, in particular the agent based method (Weiss, 1999) Agent based models allow the modeling of not only cognitively intelligent individual members (nodes) and their adaptive interpersonal relationships, but also organizational level outcomes in a dynamic and controlled setting (Axelrod, 1997). The decision to use this methodology is based not only on the necessity given the nature of this study but also on the fact that computer modeling, as an extension of human cognition (Simon, 1973) and a third symbol language besides natural language and mathematics (Ostrom, 1988) has its ....

.... also on the fact that computer modeling, as an extension of human cognition (Simon, 1973) and a third symbol language besides natural language and mathematics (Ostrom, 1988) has its unique advantages over other qualitative case studies, quantitative data analyses, and mathematical modeling (Axelrod, 1997; Taber Timpone, 1996) First of all, the problems we attempt to address involve micro macro processes with complex and adaptive relations that are often mathematically and statistically inexpressible under various organizational contexts, which are impossible to manipulate in the real ....

[Article contains additional citation context not shown here]

Axelrod, R. (1997). The complexity of cooperation: Agent-based models of competition and collaboration. Princeton, NJ: Princeton University Press.

....it is an advantage to be more complex than the opponent is, and whether noise affects this apparent advantage. We will check the robustness of the findings by performing tests on two different games. Computational techniques are used to study learning and adaptation in agentbased games, see Axelrod (1997) and Tesfatsion (1998) for a guide to the literature. A specific example that is related to this work is Miller (1996) who uses a model of learning and adaptation to analyze the coevolution of strategies in the prisoner s dilemma. These studies typically involve defining the rules of the game, ....

Axelrod, Robert. 1997. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton: Princeton University Press.

....in electricity in which arti cial adaptive agents, representing generating companies, compete to generate electricity in a partially observable constrained environment. Agents have been used to model competitors in markets [1] and players in games, particularly the iterated prisoners dilemma [2], using a variety of reinforcement learning techniques [3] Whilst the agent model presented here is related to this work, there are several key di erences concerning both the nature of the market and the restrictions placed on the agents. The UK market is administered by the National Grid ....

R. Axelrod. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princetown University Press, 1997.

No context found.

R. Axelrod. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press, 1997.

No context found.

Axelrod, R. (1997). The Complexity of Cooperation : Agent-Based Models of Competition and Collaboration, chapter 7, Disseminating Culture. Princeton University Press, Princeton, New Jersey.

No context found.

Axelrod, Robert, 1997, The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press, Princeton, NJ.

No context found.

Axelrod, R. M.: The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton University Press, 1997.

No context found.

Axelrod, R. (1997). The Complexity of Cooperation : Agent-Based Models of Competition and Collaboration, chapter 7, Disseminating Culture. Princeton University Press, Princeton, New Jersey.

No context found.

R. Axelrod, The complexity of cooperation: Age ntbased models of competition and collaboration .Prin ceton, NJ: Princeton University Press, 1997.

No context found.

Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton University Press: Princeton.

No context found.

R. Axelrod. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press, 1997.

No context found.

Axelrod, R. (1997). The Complexity of Cooperation: AgentBased Models of Competition and Collaboration. Princeton Press.

No context found.

Robert Axelrod. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press, Princeton, 1997.

No context found.

R. Axelrod. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press, New Jersey, 1997.

No context found.

R. Axelrod. The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princetown University Press, 1997.

No context found.

Axelrod, R., The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton, NJ: Princeton University Press, 1997.

First 50 documents

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC