Etxeberria A., Merelo J. J. & Moreno A. (1994) Studying organisms with basic cognitive capacities in artificial worlds. Cognitiva 3(2): 203–218. Fulltext at https://cepa.info/3929
In this paper we pose the problem of how to study basic cognitive processes in the frame of simulations of artificial worlds of the style of Artificial Life. The main difficulty of simulating biologically grounded cognitive processes lies in the search for forms of organisms suitable to establish functional relationships with their environments and coevolve with them. In order to attempt it, we study the properties of autonomous systems at different degrees of complexity and the origin of cognitive processes as a sophistication of primitive sensors-motor loops of living systems. The distinction between what we call ontogenetic adaptation to an environment and learning motivates a definition of two different degrees of complexity of that interaction. While the first one generates a variety of structures within individuals in an evolutionary scale, the second one produces a subsystem that is modulated during the life of each organism. We present some ideas to develop a model of an Artificial World where some our theoretical claims can be studied and suggest that an AL approach can arise an interesting discussion in Cognitive Science.
Moreno A., Merelo J. J. & Etxeberria A. (1992) Perception, adaptation and learning. In: McMullin B. (ed.) Proceedings of the workshop “Autopoiesis and Perception”. DCU, Dublin: 65–70. Fulltext at https://cepa.info/5235
We attempt to distinguish, in a biological frame, ontogenetical adaptation from learning. Ontogenetical adaptation arises as a second order (sensorimotor) loop on the ground of the operational closure that provides autonomy and reproductive identity to the living system. Adaptation ensures, through perception, the functional correlation between metabolic-motor states and the states of the environment. Learning brings about a qualitative change in regard to adaptation, the most generic and simple form of optimization at an individual scale. It implies the idea of new knowledge, in the sense that the organism links what formerly appeared as an undistinguished whole. In other words, it means the capability to change its own codes of meaning. Finally, we outline some basic ideas for modelling an adaptive sensor embedded in a (partially) autonomous system, which implies the former distinction between adaptation and learning.