37,587 research outputs found
Learning in evolutionary environments
Not availabl
Game theoretic aspects of distributed spectral coordination with application to DSL networks
In this paper we use game theoretic techniques to study the value of
cooperation in distributed spectrum management problems. We show that the
celebrated iterative water-filling algorithm is subject to the prisoner's
dilemma and therefore can lead to severe degradation of the achievable rate
region in an interference channel environment. We also provide thorough
analysis of a simple two bands near-far situation where we are able to provide
closed form tight bounds on the rate region of both fixed margin iterative
water filling (FM-IWF) and dynamic frequency division multiplexing (DFDM)
methods. This is the only case where such analytic expressions are known and
all previous studies included only simulated results of the rate region. We
then propose an alternative algorithm that alleviates some of the drawbacks of
the IWF algorithm in near-far scenarios relevant to DSL access networks. We
also provide experimental analysis based on measured DSL channels of both
algorithms as well as the centralized optimum spectrum management
Herbert Simon's decision-making approach: Investigation of cognitive processes in experts
This is a post print version of the article. The official published can be obtained from the links below - PsycINFO Database Record (c) 2010 APA, all rights reserved.Herbert Simon's research endeavor aimed to understand the processes that participate in human decision making. However, despite his effort to investigate this question, his work did not have the impact in the “decision making” community that it had in other fields. His rejection of the assumption of perfect rationality, made in mainstream economics, led him to develop the concept of bounded rationality. Simon's approach also emphasized the limitations of the cognitive system, the change of processes due to expertise, and the direct empirical study of cognitive processes involved in decision making. In this article, we argue that his subsequent research program in problem solving and expertise offered critical tools for studying decision-making processes that took into account his original notion of bounded rationality. Unfortunately, these tools were ignored by the main research paradigms in decision making, such as Tversky and Kahneman's biased rationality approach (also known as the heuristics and biases approach) and the ecological approach advanced by Gigerenzer and others. We make a proposal of how to integrate Simon's approach with the main current approaches to decision making. We argue that this would lead to better models of decision making that are more generalizable, have higher ecological validity, include specification of cognitive processes, and provide a better understanding of the interaction between the characteristics of the cognitive system and the contingencies of the environment
The mechanics of stochastic slowdown in evolutionary games
We study the stochastic dynamics of evolutionary games, and focus on the
so-called `stochastic slowdown' effect, previously observed in (Altrock et. al,
2010) for simple evolutionary dynamics. Slowdown here refers to the fact that a
beneficial mutation may take longer to fixate than a neutral one. More
precisely, the fixation time conditioned on the mutant taking over can show a
maximum at intermediate selection strength. We show that this phenomenon is
present in the prisoner's dilemma, and also discuss counterintuitive slowdown
and speedup in coexistence games. In order to establish the microscopic origins
of these phenomena, we calculate the average sojourn times. This allows us to
identify the transient states which contribute most to the slowdown effect, and
enables us to provide an understanding of slowdown in the takeover of a small
group of cooperators by defectors: Defection spreads quickly initially, but the
final steps to takeover can be delayed substantially. The analysis of
coexistence games reveals even more intricate behavior. In small populations,
the conditional average fixation time can show multiple extrema as a function
of the selection strength, e.g., slowdown, speedup, and slowdown again. We
classify two-player games with respect to the possibility to observe
non-monotonic behavior of the conditional average fixation time as a function
of selection strength.Comment: Accepted for publication in the Journal of Theoretical Biology.
Includes changes after peer revie
Fixation probabilities in populations under demographic fluctuations
We study the fixation probability of a mutant type when introduced into a
resident population. As opposed to the usual assumption of constant pop-
ulation size, we allow for stochastically varying population sizes. This is
implemented by a stochastic competitive Lotka-Volterra model. The compe- tition
coefficients are interpreted in terms of inverse payoffs emerging from an
evolutionary game. Since our study focuses on the impact of the competition
values, we assume the same birth and death rates for both types. In this gen-
eral framework, we derive an approximate formula for the fixation probability
{\phi} of the mutant type under weak selection. The qualitative behavior of
{\phi} when compared to the neutral scenario is governed by the invasion
dynamics of an initially rare type. Higher payoffs when competing with the
resident type yield higher values of {\phi}. Additionally, we investigate the
influence of the remaining parameters and find an explicit dependence of {\phi}
on the mixed equilibrium value of the corresponding deterministic system (given
that the parameter values allow for its existence).Comment: 31 pages, 7 figure
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