Dara Curran

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A number of learning models are commonly employed in the simulation of social behaviour. These include population learning, lifetime learning and cultural learning. Population learning allows populations as a whole to evolve over time, typically through a Darwinian model of natural selection. Lifetime learning allows individuals to acquire knowledge during(More)
Population learning can be described as the iterative Darwinian process of fitness-based selection and genetic transfer of information leading to populations of higher fitness and is often simulated using genetic algorithms. Cultural learning describes the process of information transfer between individuals in a population through non-genetic means.(More)
Evolutionary learning is a learning model that can be described as the iterative Darwinian process of fitness-based selection and genetic transfer of information leading to populations of higher fitness. Cultural learning describes the process of information transfer between individuals in a population through non-genetic means. Cultural learning has been(More)
— This paper examines the effect of the addition noise to the cultural learning process of a population of agents. Experiments are undertaken using an artificial life simulator capable of simulating population learning (through genetic algorithms) and lifetime learning (through the use of neural networks). To simulate cultural learning, (the exchange of(More)
This paper examines the effects of lifetime learning on populations evolving genetically in a series of changing environments. The analysis of both fitness and diversity of the populations provides an insight into the improved performance provided by lifetime learning. The NK fitness landscape model is employed as the problem task, which has the advantage(More)