Микроорганизмдердің бейімделу қабілеті мен интеллектуалды ұйымдасуы

Adaptive behavior by microscopic organisms including bacteria and protists
Microbial intelligence (known as bacterial intelligence) is the intelligence shown by microorganisms. The concept encompasses complex adaptive behavior shown by single cells, and altruistic or cooperative behavior in populations of like or unlike cells mediated by chemical signalling that induces physiological or behavioral changes in cells and influences colony structures. Complex cells, like protozoa or algae, show remarkable abilities to organize themselves in changing circumstances. Shell building by amoebae reveals complex discrimination and manipulative skills that are ordinarily thought to occur only in multicellular organisms. Even bacteria can display more behavior as a population. These behaviors occur in single species populations, or mixed species populations. Examples are colonies or swarms of myxobacteria, quorum sensing, and biofilms. It has been suggested that a bacterial colony loosely mimics a biological neural network. The bacteria can take inputs in form of chemical signals, process them and then produce output chemicals to signal other bacteria in the colony. Bacteria communication and self organization in the context of network theory has been investigated by Eshel Ben Jacob research group at Tel Aviv University which developed a fractal model of bacterial colony and identified linguistic and social patterns in colony lifecycle.

Individual cells of cellular slime moulds coordinate to produce complex structures or move as multicellular entities. The single celled ciliate Stentor roeselii expresses a sort of "behavioral hierarchy" and can 'change its mind' if its response to an irritant does not relieve the irritant, implying a very speculative sense of 'cognition'. Paramecium, specifically P. caudatum, is capable of learning to associate intense light with stimulus such as electric shocks in its swimming medium; although it appears to be unable to associate darkness with electric shocks. Protozoan ciliate Tetrahymena has the capacity to 'memorize' the geometry of its swimming area. Cells that were separated and confined in a droplet of water, recapitulated circular swimming trajectories upon release. This may result mainly from a rise in intracellular calcium.

Bacterial colony optimization is an algorithm used in evolutionary computing. The algorithm is based on a lifecycle model that simulates some typical behaviors of E. coli bacteria during their whole lifecycle, including chemotaxis, communication, elimination, reproduction, and migration.

Logical circuits can be built with slime moulds. Distributed systems experiments have used them to approximate motorway graphs. The slime mould Physarum polycephalum is able to solve the Traveling Salesman Problem, a combinatorial test with exponentially increasing complexity, in linear time.

Microbial community intelligence is found in soil ecosystems in the form of interacting adaptive behaviors and metabolisms. According to Ferreira et al., "Soil microbiota has its own unique capacity to recover from change and to adapt to the present state[ ] [This] capacity to recover from change and to adapt to the present state by altruistic, cooperative and co occurring behavior is considered a key attribute of microbial community intelligence." Many bacteria that exhibit complex behaviors or coordination are heavily present in soil in the form of biofilms. The complicated interaction of microbes in the soil has been proposed as a potential carbon sink. Bioaugmentation has been suggested as a method to increase the 'intelligence' of microbial communities, that is, adding the genomes of autotrophic, carbon fixing or nitrogen fixing bacteria to their metagenome.