Narrow Results

A knowledge base is an important notion of rough set theory. A tolerance knowledge base is its generalization. Measures of uncertainty as important evaluation tools in the fields of machine learning can measure the dependence and similarity between two targets. This paper investigates uncertainty measurement for a tolerance knowledge base by using its knowledge structure. The knowledge structure of a given tolerance knowledge base is first introduced by means of set vectors. Then, the dependence and independence between knowledge structures of tolerance knowledge bases are depicted. Next, the measurement uncertainty of tolerance knowledge bases is investigated. Finally, to obtain two tolerance knowledge bases with additional data, two information systems from the UCI Repository of machine learning databases are selected to construct two numerical experiments, and an effectiveness analysis is performed from the perspective of statistics to show the feasibility of the proposed measures.

The paper is mainly dealing with the dilemma between knowledge creation incentives and knowledge diffusion. Knowledge is modeled as a structure, which is expanding through agents' creation behaviors, and becomes "locally" available to other agents once it is disclosed. An agent taken randomly at each period of the discrete time is choosing between the acquisition of an accessible piece of knowledge and the creation of one. Knowledge value being a decreasing function of the number of agents sharing it, a higher (exogenous and tunable) rate of disclosure decreases the incentives to create (in increasing the diffusion speed). Using simulations, we show that there is, for each set of values of the different parameters, a non null optimal rate of disclosure (maximizing the collective performances of the set of agents) and discuss the effect of some of the structural parameters on it.

Creation has been regarded as the most valuable advantage of corporations since the 1990s. However, team creation generally lacks effective support methods and support tools at present. It is important to research how to support team creation. In this paper, we design a system to support team creation, the main functions of which are team information record, knowledge visualization, and information relationship recognition.

The inherent micro-structure (agent-agent/system) of human organizations has been introduced in Chapters 2 and 3. Fundamentally, human organizations are composite complex adaptive systems with human beings as interacting agents (each an intrinsic complex adaptive system). This chapter further analyzes the basic conceptual foundation of the multi-layer structure, including advantages of the intelligent biotic macro-structure (with inherent features similar to that of an intelligent biological being — a structural reform), and its unique and more integrative complex adaptive dynamic in intelligent human organizations (towards iCAD). The necessity of nurturing an intelligent biotic macro-structure with vital characteristics that better synchronize and enhance sophisticated information/knowledge-related activities is highly beneficial — achieving a higher structural capacity. Thus, the attributes, functions and higher structural capacity of the more intelligent biotic macro-structure can reinforced the competitiveness of any categories of human organizations extensively.

In this respect, connecting and engaging of intelligence/consciousness sources (individual and collective), organizing around intelligence, intelligence/ consciousness management, and the intelligent biotic macrostructure are mutually enhancing (towards higher coherency). Apparently, being intelligence/consciousness-centric is a beneficial and critical activator (strategic foundation) of the intelligence paradigmatic shift. In the present context, the roles and integration of intelligence, information and knowledge, as well as nurturing a ‘common’ language and elevating coherency in human organizations (with respect to the macro-structure and micro-structure, as well as their higher collectiveness — collectiveness capacity) must be more deeply scrutinized and utilized. The presence and significance of the individual intelligence enhancer encompassing three entities namely, intelligence, knowledge, and theory in the human thinking systems, and the necessity of nurturing a similar and effective intelligence enhancer at organizational level are analyzed. Subsequently, the supporting roles and contributions of artificial intelligence systems are also examined.

In between the macro-structure and micro-structure are two meso-structures. In the intelligent organization theory, the complexity meso-structure encompasses spaces of complexity and punctuation points. In this respect, complexity is a highly significant focal point, and the exploitation of co-existence of order and complexity is a new necessity (complexity-centricity). Next, the network meso-structure encompassing complex network (network of networks) is also an inherent structure and dynamic in all human organizations. This meso-structure is briefly introduced, and will be more deeply analyzed with respect to governance (network-centricity, network governance).

Hence, it is crucial to lead and manage human organizations with a strategic approach that integrates the above multi-layer structure/ dynamic at all time so that a higher structural capacity, collectiveness capacity, adaptive capacity, self-organizing capacity, and emergence-intelligence capacity can be nurtured. In the current highly competitive context, possessing these positive capabilities to elevate coherency and synergetic characteristics (including social consensus and the construal aspect) and dynamic is also highly crucial — a key focus of the complexity-intelligence strategy (towards achieving higher organizational mental cohesion). Hence, the significance and impact of nurturing intelligent human organizations with the complexity-intelligence-centric and network-centric approach that leads to the emergent of smarter evolvers and emergent strategists must be better understood and adopted. (The conceptual foundation on structural-dynamic coherency and synergy in intelligent human organizations developed in this chapter will be more deeply reviewed and exploited in later chapters.)

This chapter focuses on establishing the conceptual foundation of the macroscopic perspective (structure and processes) of human thinking systems—the conceptualization of the general information theory (a component of the complexity-intelligence strategy). In this analysis, the human thinking system is perceived to be comprised of two components namely, the energy–matter subsystem (the natural component), and the physical symbol subsystem (an artificial component unique to humanity). The general procedure in which the human mind handles and exploits one or more physical symbol systems (symbols manipulation) is analyzed. The conceptual development encompassing the creation of the character set, capturing and transformation of data and information, acquisition of knowledge and emergent of wisdom (the four external entities), and the significance of a written language, as well as the additional associated functions are investigated.

The unique ability of creating a character set is confined to humanity indicating that human thinking systems are the most intense intelligence sources on this planet. The intrinsic and interactive properties of the character set and the language depict the characteristics and sophistication/ complexity of the physical symbol system. Besides interacting among themselves (data, information, knowledge and wisdom), these external entities also interact with the natural entities, the information-coded energy quanta, according to certain rules and principles. Subsequently, the energy quanta interact with the information-coded matter structure (the brain’s complex neural network). This unique ability (the presence of a written language) allows knowledge to be stored externally, and abstract concepts (including theory) and complex strategizing to emerge for the first time in the human world. In this respect, in the intense human intelligence source (individual or collective), information and knowledge exists in physical, energy and matter forms, and they are inter-convertible (internalization and externalization). The interactions among the six entities and the conversion from one form to another vividly review the presence of the uniqueness of the human thinking system, as well as the orgmind — greatly redefining the interactions and dynamic in the humanity and its organizations.

Subsequently, the boundaries and objectives of human thinking systems as information processing systems, and the necessity of artificial information systems are conceived as four postulates. In the intelligent organization theory, a deeper comprehension of the human thinking systems (complex adaptive systems) is vital, as they are the vital assets closely associated with the nurturing of highly intelligent human organizations (iCAS), including the coherency and contributions of a multi-layer intelligent structure (intelligent biotic macro-structure and agent-agent/system micro-structure). In this respect, the cognitive perspective must be better comprehended and utilized.

The basic foundation of intelligent complex adaptive dynamic (iCAD) exploits the interdependency of five significant attributes of intelligent human organizations (iCAS) that possess certain unique characteristics only associated with human organizations. The attributes involved are collective intelligence, connectivity, culture (mindful), organizational learning, and knowledge management, and their integrative structure and dynamics. This foundation pillar of the iCAD is conceived as the 3C-OK framework. Recognizing the necessity of this integrated and redefined foundation of the intelligent human complex adaptive dynamic is vital, as this set of attributes is not present (minimal) in other complex adaptive systems (CAS). In this respect there are differences between highly intelligent human adaptive dynamic (iCAD) and other biological complex adaptive dynamics (CAD). A primary factor that created the difference is the mental function of orgmindfulness. Thus, the characteristics and capabilities of human collective intelligence are substantially different from swarm intelligence. In this respect, the high intelligenceintelligence linkages which are strongly correlated with collective intelligence [determined by the characteristics of the agents’ abstract mental space (including a space for deeper contemplation)], and org-consciousness and the relational parameter (relational capacity) are new significant focal points (an intelligent human organization <=> at least a thinking system + feeling system).

In the intelligent organization theory, the integrated 3C-OK structure and dynamic is mutually enhancing with organizing around intelligence and the intelligent biotic macro-structure. The framework supports the elevation of the collectiveness capacity and adaptive capacity which are key capacities of intelligent human organizations. In particular, their interdependency illustrates that organizational learning and knowledge management (a vital capability associated with the creation of an intangible abstract mental space in the human world) cannot be executed effectively in any human organizations without the presence of the other three attributes. Hence, human interacting agents, each an intense intelligence/consciousness source, and embedded with a set of changing nonlinear behavioral schemata, and their linkages (including the social cognition and construal perspective that influence the self-transcending constructions capability, and emergence-intelligence capacity of the organization) must be well-exploited. In this respect, the integrated 3C-OK structure provides the basic strata of the iCAD. Thus, an organization that places sufficient emphasis on the integrated 3C-OK structure and dynamic will gradually experience the emergence of a higher level human iCAD. The presence of such an environment also facilitates faster and better responses to unexpected changes.

The basic foundation of the intelligent organization theory is conceptualized in this chapter. The significance of intelligence and organizing around intelligence, intelligence management and the general biotic structure of an intelligent human organization and its benefits are further discussed. The roles of intelligence, information and language in a human organization are examined. The presence and necessity of nurturing an effective intelligence enhancer encompassing three entities, namely, intelligence, knowledge and theory in the human thinking systems is introduced. The concepts on the space of order and the space of complexity are also shared. Some fundamental aspects of the deliberate strategy and emergent strategy are further examined. The above concepts are developed with respect to the fact that the human minds and human organizations are nonlinear complex adaptive systems. Consequently, the intelligent organizations that emerge are smarter evolvers.

This chapter focuses on the macroscopic perspective of the human thinking system. The human thinking system is perceived to be comprised of two sub-components namely, the energy–matter subsystem and the physical symbol subsystem. The procedure in which the human mind handles one or more physical symbol systems is discussed. The conceptual development encompasses the transformation of data, information, knowledge and wisdom, and how a language emerges. The boundary of a human thinking system and the necessity of artificial information systems are also included. A better understanding of the human thinking system and the conceptualization of the general information theory is vital to the nurturing of highly intelligent human organizations.

This chapter introduces the roles and needs of artificial information systems networks in intelligent human organizations. These artificial networks improve the efficiency of the physical structure of human organizations by increasing the speed of information processing and transmission, elevating the capacity of knowledge storage externally, and improving the quality of connectivity and organizational learning. To a great extent, the artificial intelligent information networks enhance the efficiency of the equivalent of the central nervous system in highly intelligent biological beings, including the sensory subsystem. The common intelligent artificial information systems and their roles and functions are briefly discussed.