SpaceConnect: A Framework for Modelling and Managing Behavioral States of Evolutive Agents

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.