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1981 Naylor's Ph.D. thesis provided a full development of both BSP trees and a graph-theoretic approach using strongly connected components for pre-computing visibility, as well as the connection between the two methods. BSP trees as a dimension-independent spatial search structure were emphasized, with applications to visible surface ...
Brain simulation projects intend to contribute to a complete understanding of the brain, and eventually also assist the process of treating and diagnosing brain diseases. [ 2 ] [ 3 ] Simulations utilize mathematical models of biological neurons , such as the hodgkin-huxley model , to simulate the behavior of neurons , or other cells within the ...
An artificial brain (or artificial mind) is software and hardware with cognitive abilities similar to those of the animal or human brain. [1] Research investigating "artificial brains" and brain emulation plays three important roles in science: An ongoing attempt by neuroscientists to understand how the human brain works, known as cognitive ...
BSP has been extended by many authors to address concerns about BSP's unsuitability for modelling specific architectures or computational paradigms. One example of this is the decomposable BSP model. The model has also been used in the creation of a number of new programming languages and interfaces, such as Bulk Synchronous Parallel ML (BSML ...
While the computer metaphor draws an analogy between the mind as software and the brain as hardware, CTM is the claim that the mind is a computational system. More specifically, it states that a computational simulation of a mind is sufficient for the actual presence of a mind, and that a mind truly can be simulated computationally.
Diffusion-limited aggregation (DLA) is the process whereby particles undergoing a random walk due to Brownian motion cluster together to form aggregates of such particles. . This theory, proposed by T.A. Witten Jr. and L.M. Sander in 1981, [1] is applicable to aggregation in any system where diffusion is the primary means of transport in the sy
This field of study has its historical roots in numerous disciplines including machine learning, experimental psychology and Bayesian statistics.As early as the 1860s, with the work of Hermann Helmholtz in experimental psychology, the brain's ability to extract perceptual information from sensory data was modeled in terms of probabilistic estimation.
The Boltzmann brain gained new relevance around 2002, when some cosmologists started to become concerned that, in many theories about the universe, human brains are vastly more likely to arise from random fluctuations; this leads to the conclusion that, statistically, humans are likely to be wrong about their memories of the past and in fact ...