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Émile Coué identified two very different types of self-suggestion: . intentional, "reflective autosuggestion": made by deliberate and conscious effort, andunintentional, "spontaneous auto-suggestion": which is a "natural phenomenon of our mental life … which takes place without conscious effort [and has its effect] with an intensity proportional to the keenness of [our] attention".
The prominent feature of systems with self-adjusting parameters is an ability to avoid chaos. The name for this phenomenon is "Adaptation to the edge of chaos" . Adaptation to the edge of chaos refers to the idea that many complex adaptive systems (CASs) seem to intuitively evolve toward a regime near the boundary between chaos and order. [ 19 ]
The weights are adjusted according to some learning rule or algorithm, such as Hebbian learning. [9] Most of the variety among the models comes from: Interpretation of units: Units can be interpreted as neurons or groups of neurons. Definition of activation: Activation can be defined in a variety of ways.
The functions of consciousness suggested by Baars are: definition and context setting, adaptation and learning, editing, flagging and debugging, recruiting and control, prioritizing and access-control, decision-making or executive function, analogy-forming function, metacognitive and self-monitoring function, and autoprogramming and self ...
Those who are unable to adjust well are more likely to have clinical anxiety or depression, [3] as well as experience feelings of hopelessness, anhedonia, difficulty concentrating, sleeping problems, and reckless behavior. [4] In psychology, "adjustment" can be seen in two ways: as a process and as an achievement.
In an adaptive system, a parameter changes slowly and has no preferred value. In a self-adjusting system though, the parameter value “depends on the history of the system dynamics”. One of the most important qualities of self-adjusting systems is its “adaptation to the edge of chaos” or ability to avoid chaos.
Heuristics (from Ancient Greek εὑρίσκω, heurískō, "I find, discover") is the process by which humans use mental shortcuts to arrive at decisions. Heuristics are simple strategies that humans, animals, [1] [2] [3] organizations, [4] and even machines [5] use to quickly form judgments, make decisions, and find solutions to complex problems.
The Hopcroft–Tarjan planarity testing algorithm was the first linear-time algorithm for planarity testing. [11] Tarjan has also developed important data structures such as the Fibonacci heap (a heap data structure consisting of a forest of trees), and the splay tree (a self-adjusting binary search tree; co-invented by Tarjan and Daniel Sleator).