In the natural world, all objects and entities (agents)
evolves and changes their state continually e.g. a village may become
"Town". To capture and depict the evolution of agents, a commonly
used approach is the utilization of a multi-dimensional model. This model is
used in most of traditional and highly powerful analytical systems which data
are being represented in multi-dimensional data structure, enabling efficient
data tracking and monitoring. Such systems are popular in organizations and
institutions that store and interpret historical cumulative data for
forecasting and decision-making purposes, such as data warehousing. However,
when dealing with unconventional evolutionary spaces, handling and representing
the agent’s evolution using a multi-dimensional model becomes challenging. One
of the key challenges lies in managing reactive and dynamic data, which are
being more specified and solicited, and may include and stimulate a massive
amount of knowledge. In this chapter, a meticulous/methodical framework is
proposed for modeling and managing of evolving agents or structural entities
(metaphors, e.g. Restaurants, Hospitals, Factories, etc.). These agents can
exist within the same or different spaces (as organizational structures); they
evolve, interact and transit. They are inter-dependent, and have analytical
state-full characteristics (so far, seen as expressive dimensions). The
framework provides solutions for analysis and prediction, along with an
analytical methodology support that shows; how agents evolve, how evolutions
propagate, how evolutions stimulate the evolution of other agents etc. The
chapter extensively discusses the fundamental features, principles, and
foundations that illustrated in preceding work “hyper-space navigational
framework renovated with SpaceConnect”, and also experimented with an
indicative case study.
Author(s) Details:
Mohamed Dbouk,
Faculty of Sciences (I), Lebanese University, Beirut, Lebanon.
Hamid Mcheick,
Université
du Québec à Chicoutimi, Québec, Canada.
Ebrahim Al-Almani,
Doctoral School of Science and Technology, Lebanese University,
Beirut, Lebanon and Faculty of Science & Engineering, The National
University, Sana’a, Yemen.
Please see the link here: https://stm.bookpi.org/RATMCS-V8/article/view/13074
