4,248 research outputs found
Analytical models for well-mixed populations of cooperators and defectors under limiting resources
In the study of the evolution of cooperation, resource limitations are
usually assumed just to provide a finite population size. Recently, however,
agent-based models have pointed out that resource limitation may modify the
original structure of the interactions and allow for the survival of
unconditional cooperators in well-mixed populations. Here, we present
analytical simplified versions of two types of agent-based models recently
published: one in which the limiting resource constrains the ability of
reproduction of individuals but not their survival, and a second one where the
limiting resource is necessary for both reproduction and survival. One finds
that the analytical models display, with a few differences, the same
qualitative behavior of the more complex agent-based models. In addition, the
analytical models allow us to expand the study and identify the dimensionless
parameters governing the final fate of the system, such as coexistence of
cooperators and defectors, or dominance of defectors or of cooperators. We
provide a detailed analysis of the occurring phase transitions as these
parameters are varied.Comment: 7 pages, 8 figure
Neural Network Local Navigation of Mobile Robots in a Moving Obstacles Environment
IF AC Intelligent Components and Instruments for Control Applications, Budapest, Hungary, 1994This paper presents a local navigation method based on generalized predictive control. A modified cost function to avoid moving and static obstacles is presented. An Extended Kaiman Filter is proposed to predict the motions of the obstacles. A Neural Network implementation of this method is analysed. Simulation results are shown.Ministerio de Ciencia y Tecnología TAP93-0408Ministerio de Ciencia y Tecnología TAP93-058
Fuzzy Predictive Controller for Mobile Robot Path Tracking
IFAC Intelligent Components and Instruments for Control Applications, Annecy, France 1997This paper presents a way of implementing a Model Based Predictive Controller (MBPC) for mobile robot path-tracking. The method uses a non-linear model of mobile robot dynamics and thus allows an accurate prediction of the future trajectories. Constraints on the maximum attainable angular velocity is also considered by the algorithm. A fuzzy approach is used to implement the MBPC. The fuzzy controller has been trained using a lookup-table scheme, where the database of fuzzy-rules has been obtained automatically from a set of input-output training patterns, computed with the predictive controller. Experimental results obtained when applying the fuzzy controller to a TRC labmate mobile platform are given in the paper.Ministerio de Ciencia y Tecnología TAP95-0307Ministerio de Ciencia y Tecnología TAP96-884C
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