Updates:
2008-01-30: Chapter 5, Chapter 6, preface, book summary2008-01-26: Chapter 3, Chapter 4
2008-01-23: Chapter 1, Chapter 2
2008-01-17: book summary, preface
Preface
This E-book is an attempt to establish a theory that identifies the commonality behind various forms intelligence, including human intelligence, machine intelligence, animal intelligence, alien intelligence, community intelligence, etc.
This theory is part of an on-going AI project, together with a formal model built according to the theory, and a computer implementation of the formal model.
This E-book consists of a main text and many sidebars. The main text is organized into webpages at three levels: book, chapter, and section, where each topic is summarized in a high-level file, as well as discussed with more details in a low-level file. A sidebar covers a special topic, and is linked from the main text.
Chapter 1. Information System
To treat a system as an information system means to describe it at an abstract level, so as to omit the concrete processes underneath.
The internal structure of every information system can be analyzed in terms of its goals, actions, and beliefs.
An information system carries out its actions to achieve its goals, following the relations among them as provided by its beliefs. The system's internal process cost time-space resources.
Chapter 2. Intelligent System
Information systems can be divided into instinctive systems and intelligent systems.
In an instinctive system, all major components are determined when the system is formed, and remain unchanged afterwards.
In an intelligent system, all major components are adaptive to the environment. The system learns new beliefs, organize actions into skills, derive new goals, all as attempts to improve its goal-achieving capability, under the assumption that in general the future will be similar to the past.
Chapter 3. Inference System
To discuss an information systems in a more accurate manner, it is necessary to put it into a formalization framework. For advanced intelligent systems, the framework of an inference system is more suitable than the alternatives, because of its expressing and processing power.
An inference system can be pure-axiomatic, semi-axiomatic, or non-axiomatic. Many problems in the traditional logistic AI can be attributed to their axiomatic nature, and therefore become solvable in a non-axiomatic system.
A concrete intelligent inference system, NARS, is designed to be non-axiomatic. Consequently, its goals, actions, and beliefs are represented and processed in a way that is fundamentally different from how they are handled in traditional inference systems.
Chapter 4. Self-Organizing Process
For a system like NARS, its running process is a self-organizing process, in which the system reorganize its goals, actions, and beliefs, according to its experience.
Self-organization of goals forms and evolves the system's goal structure. In the process, goals are derived, evaluated, prioritized, and removed.
Self-organization of actions means the acquiring of new skills as "programs" of existing actions and skills, as well as the building and applying of tools.
Self-organization of beliefs produces more accurate, compact, and useful summary for the system's experience.
Self-organization of concepts provides an intermediate level of structure between the whole memory and the individual items.
Chapter 5. Experience and Socialization
The beliefs and goals of advanced intelligent systems come both from personal experience (via is sensorimotor mechanism) and from social experience (via its language processing mechanism).
The sensorimotor mechanism implements the actions of an information system, and handles the direct interaction between a system and its environment. Based on it, advanced systems also have a communication mechanism, which uses a language, and is carried out by the cooperation between the system and some other systems in the environment.
In an intelligent system, sensorimotor and language processing are both based on the beliefs learned by the general-purpose intelligence of the system, though the content of the beliefs is modality-specific.
Advanced intelligent systems have a separate sensorimotor mechanism on the system itself, which works in the same way as the sensorimotor mechanism on the outside world, though using different sensors and motors. Self-monitor and self-control provide the foundation of consciousness.
Socialization is the adaptation process that increases the overlap between personal beliefs/goals and shared beliefs/goals. Education is a special form of socialization, in which teachers have some control on the social experience of the students.
Chapter 6. Community and Science
A community is a group of information systems that share the same physical and social environment. Very often, a community as a whole can be treated as an information system, whose goals, actions, and beliefs coming from those of its members, though in a complicated manner.
A community can have different internal social structures, in which members may play different roles, and the information processing activities follow different procedures.
Community beliefs take the form of common sense, custom, religion, or science. Science is organized common experience that can be used to guide the members in the future. The development of science follows the same logic as the self-organization of beliefs in an individual system.
Community actions are developed through cooperation of the members, as well as through the development of technology, which is tool building and applying at the level of a society.
Common goals take the form of ethics, ideology, or religion, which normally is consistent with the individual goals overall.
Science is common, systematic, and predicative knowledge. Its development follows the same logic as the beliefs in an intelligent system.