The Idea of Defeasibility

In a very broad sense, the idea of defeasibility may be applied to any process that responds to its normal inputs with certain outcomes (the default results), but which delivers different outcomes when such inputs are augmented with further, exceptional or abnormal elements.
The computer scientist and theorist of complexity John Holland argues that complex systems—such as a cell, an animal, or an ecosystem—can be characterised “in terms of a set of signal-processing rules called classifier rules” (Holland 2012, 28). Each such rule represents a mechanism which “accepts certain signals as inputs (specified by the condition part of the rule) and then processes the signals to produce outgoing signals (the action part of the rule).” He observes that complex systems need to address different situations, requiring different responses, which are triggered by rules having different levels of generality. In many cases the most efficient way to cover multiple different contingencies consists in constructing “a hierarchy of rules, called a default hierarchy, in which general rules cover the most common situations and more specific rules cover exceptions” (Holland et al 1989). Thus, a general rule would provide the normal response to a certain input, but more specific rules would override the general rule in exceptional situations, in which a different response is needed. The emergence of default hierarchies may be favoured by evolution, since such hierarchies may contribute to the fitness of the systems using them.
Default hierarchies offer several advantages to systems that learn or adapt:
This perspective can be applied to different domains at different levels of abstraction. For instance, at the cellular level rule mechanisms specify the catalytic and anti-catalytic processes that induce and inhibit chemical reactions. At the DNA level, rule mechanisms are provided by genes (and parts of them): a gene delivers the protein matching the sequence of the gene’s bases. A gene may be regulated by other genes that send signals that under particular conditions repress (turn off) or induce (turn on) the functioning of the gene rule at issue. Animal behaviour is also largely governed by systems of reflex rules defining reactions to heat or cold; or to the sight, smell, or taste of food; or to the perception of incoming dangers; and so on. Such reflexes can be innate or learned by experience, i.e., by conditioning and reinforcement. They may interact in complex patterns where some reflexes are stronger than others, so that they determine the response in cases of conflict, or they may have an inhibitory impact on other reflexes, blocking them under particular situations. In humans, reflexes are integrated with deliberative processes and means-end reasoning, but still they govern a large part of human behaviour.
As Holland et al. (1989, 38) argue, not only instinctive reflexes but also mental models can be based on sets of prioritised default rules:
In conclusion, a defeasible process can be as characterized a mechanism which responds to its normal inputs with certain default outcomes, but that may fails to respond in this way, when the input is accompanied by certain additional exceptional elements.