Antes de Memmo, mis apuntes estaban dispersos en PDFs. Ahora, un espacio de trabajo lo reúne todo y veo exactamente lo que me queda por estudiar.
The notion of swarm intelligence was introduced for describing decentralized and self-organized behaviors of groups of animals. Then this idea was extrapolated to design groups of robots which interact locally to cumulate a collective reaction. Some natural examples of swarms are as follows: ant colonies, bee colonies, fish schooling, bird flocking, horse herding, bacterial colonies, multinucleated giant amoebae Physarum polycephalum, etc. In all these examples, individual agents behave locally with an emergence of their common effect.
An intelligent behavior of swarm individuals is explained by the following biological reactions to attractants and repellents. Attractants are biologically active things, such as food pieces or sex pheromones, which attract individuals of swarm. Repellents are biologically active things, such as predators, which repel individuals of swarm. As a consequence, attractants and repellents stimulate the directed movement of swarms towards and away from the stimulus, respectively.
It is worth noting that a group of people, such as pedestrians, follow some swarm patterns of flocking or schooling. For instance, humans prefer to avoid a person considered by them as a possible predator and if a substantial part of the group in the situation of escape panic (not less than 5%) changes the direction, then the rest follows the new direction, too. Some swarm patterns are observed among human beings under the conditions of their addictive behavior such as the behavior of alcoholics or gamers.
The methodological framework of studying swarm intelligence is represented by unconventional computing, robotics, and cognitive science. In this book we aim to analyze new methodologies involved in studying swarm intelligence. We are going to bring together computer scientists and cognitive scientists dealing with swarm patterns from social bacteria to human beings. This book considers different models of simulating, controlling, and predicting the swarm behavior of different species from social bacteria to humans.
Antes de Memmo, mis apuntes estaban dispersos en PDFs. Ahora, un espacio de trabajo lo reúne todo y veo exactamente lo que me queda por estudiar.
Los resúmenes de Memmo son oro antes de los exámenes. No tengo que releer 800 páginas dos semanas antes, solo las partes importantes.
El chat de IA me ha salvado la noche antes de un examen más de una vez. Sigo preguntando hasta que lo entiendo, sin esperar a que un grupo de estudio responda.
Los cuestionarios aciertan exactamente lo que necesito saber. Memmo registra dónde me atasco, así que solo practico lo que vale la pena.
Las flashcards con repetición espaciada son magia. Memmo sabe cuándo estoy a punto de olvidar algo y me lo recuerda.
Los pódcasts de IA son mis favoritos. Los escucho de camino a la universidad y obtengo un resumen sin tener que sentarme frente a un ordenador.
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