Magos-it is a collabaratioj of five networks which work together as one.
Each network has its various qualities so it makes accurate predictions.
Modular architecture is the backbone of Magos.Because it supports upgrades and development of thr new features as well as.
So Magos is prescibed by everyone.
Melius — it is the network that auto-tunes various hyperparameters, basing his
adjustments on overall MAGOS performance and changes of external
environment.
Ariolus —it is the network that combines the output from all other networks and
makes an accurate prediction, based on multiple data layers.
Galaxia — it is a data mining and classification network with noise reduction.
It gives information to higher-level networks. Smart plugins collect data
from AP|s. web and other sources
Obelus —it is a network that employs various rulesets and add-ons, such as
volatility evaluation, information sufficiency or malicious activity detection,
allowing avoidance of high uncertainty level events
Strategus — it is the risk-management network that maintains optimal investment
growth.
It uses a advanced modular architecture that supports upgrades and
development of new features.
As the main goal of Magos is to achieve the best possible forecasting accuracy.
So here are the solutions provided by Magos-
-as to achieve the best possible forecasting.it is clear
how essential the (Gf) is (as well as other key factors described by Tetlock).
we have to find an approach which allows us to perform certain tasks:
To have a very high level of (Gc), including the level of depth in a specialized domain — it can be achieved by not only having a multiple data
mining sources and noise reduction,
but also it requires a custom non-public databases.
To combine the high (Gf) starting point found in human expertise, with the
stability and self—evolvement of neural networks —
it Can be done by
blueprinting the knowledge of experts in a given domain and
transferring it to data shards inside a specific module.
To integrate self— the evolvement and constant upgrades into the system —covered by the collaboration of networks, modular architecture, and the
release of the Melius network which is responsible for the auto-tuning and
performance monitoring.
To avoid the all kinds of cognitive biases in a forecasting process — resolved by transferring the data analysis from human experts to neural networks.
In conclusion, the collaboration of neural networks in our current implementation allows us to reach the highest possible forecasting performance
with the high level of sustainability, by covering all the key traits that (superforecasters) possess.
Edge seeking-Edge is an advantage a forecaster has over the oddsmakers.
The main problem for every forecaster is to gain the advantage over whoever is
laying their bet, whether that is a prediction market, sportsbook, exchange or
other party This is called (getting an edge)
-Then odds are assigned to a particular event, the oddsmakers are indicating
what they think the likelihood of a given outcome is. If forecaster thinks that an
event — like a team winning the game or covering the spread — is more likely Than the oddsmakers do then he would have an edge.
-So betting on long terms makes a profit.
As a result everyone should connect with Magos.
Image source : 1,2,3,4
Thank you
