Adaptive individuals in evolving populations: models and algorithms
Adaptive individuals in evolving populations: models and algorithms
Adaptive individuals in evolving populations
The influence of learning on evolution
Adaptive individuals in evolving populations
How learning can guide evolution
Adaptive individuals in evolving populations
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Learning as a Consequence of Selection
Selected Papers from the 5th European Conference on Artificial Evolution
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The law of effect is a very simple law which relates the probability of emission of a behavior by a living being to the consequences of the emission of this behavior by this living being in the past. As such, this law models very basic learning. This law can be considered as an experimental fact as far as it has been observed for a whole range of living beings including human beings. In this paper, we first show that this general law can be the result of a selection process such as natural selection. Then, we show that the implementation of this law can lead to the design of adaptive systems which can mimic very closely the way a new-born develops coordinated movements. To sum-up, we show that the ability to learn such coordinated movements and exhibit adaptive behaviors can result from a multi-stage process of selection.