Page:Advanced Automation for Space Missions.djvu/64

 Hypothesis formation and learning have emerged as central problems in machine intelligence, representing perhaps the primary technological prerequisites for automated deep space exploration.

The Titan, outer planet, and interstellar missions discussed by the Space Exploration Team require a machine intelligence system able to autonomously conduct intensive studies of extraterrestrial objects. The artificial intelligence capacity supporting these missions must be adequate to the goal of producing scientific knowledge regarding previously unknown objects. Since the production of scientific knowledge is a high-level intelligence capability, the AI needs of the missions may be defined as "advanced-intelligence machine intelligence," or, more briefly, "advanced machine intelligence."

3.3.1 A Working Definition of Intelligence

Before an advanced machine intelligence system can be developed and implemented, the concept must be precisely defined and translated into operational terms. One way of doing this is to specify the patterns of inference which constitute the high-level intelligence - the design goal for advanced AI systems. Optimally, designers would have at their disposal an ideal definition of "intelligence" stating the necessary and sufficient conditions for achieving their goal. Such a definition, in addition to precisely stating what intelligence is, also would provide a set of criteria with which to decide the question: "Does entity X possess intelligence?" Unfortunately, no generally accepted ideal definition of intelligence is yet available.

However, a working definition sufficient for the purposes of the present investigation can be formulated. This inquiry addresses the general question of the characteristics of an advanced machine intelligence system needed for autonomous space exploration missions. As such, the investigation should address two questions in particular: "What intelligence capabilities must be designed into space exploration systems?" and "By what criteria will it be determined whether or not the final system actually possesses the high- level intelligence required for the mission?"

American Pragmatism, the major school of American philosophy, developed an acount of intelligence that contains the key to a useful working definition (Davis, 1972; Dewey, 1929, 1938; Fann, 1970; Mead, 1934, 1938; Miller, 1973; Peirce, 1960, 1966; and Thayer, 1968). The major figures of this school - John Dewey, William James, George Herbert Mead, and Charles Sanders Peirce - claimed that an entity's intelligence consists of its ability to reduce the complexity and variety of the world to patterns of order sufficient to support successful action by that entity. For example, human beings have reduced their welter of sensations to patterns of order, e.g., in comparative distinctions between nutrients and non-nutrients, chemical qualitative analysis schemes, and abstract aesthetic concepts. These patterns are, in turn, the bases of human actions including (following the above examples) satisfaction of the need for food, identification of an unknown chemical compound, and the creation of a work of art.

The Pragmatists further claimed that these action-related patterns of order exhaust an entity's knowledge. In other words, all knowledge is action-related - indeed, according to Peirce, "to have a belief is to be prepared to act in a certain way." This view is summarized in the fundamental Pragmatist principle that intelligence is always displayed in action and can be detected only in action. In this view intelligence is a dynamic process, rather than a static state, having at least two dimensions. First, unless an entity has a continuing history of action its intelligence is not displayed, cannot be detected, and therefore cannot be presumed to exist. Second, since a given pattern of order is linked to a related type of action, the success or failure of a particular action reflects on the "correctness" of the underlying pattern of order. An entity can have a continuing history of successful activity only if it can modify or replace those patterns of order which lead to failure. Therefore, an entity's intelligence is far more than merely the possession of a fixed stock of knowledge - even when this knowledge consists of action-related patterns of order. Rather, intelligence is the ability to preserve a high ratio of successful to unsuccessful outcomes.

The Pragmatists' account of intelligence can be summarized by this definition: Intelligence is the ability to formulate and revise patterns of order, as evidenced by the eventual emergence of successful over unsuccessful actions. There may well be aspects of intelligence that escape the definition, but nevertheless it provides a useful framework for the present investigation. This is because it focuses on capabilities which must be designed into advanced machine intelligence systems required for autonomous space exploration, as well as on the criteria with which to test for the presence of these capabilities.

A working definition of "advanced machine intelligence" in the context of autonomous scientific investigation of extraterrestrial objects can be formulated by utilizing the above general definition. The Pragmatists held that intelligence is a matter of degree and that among biological entities the question is never intelligence versus nonintelligence, but rather the level thereof. The actions by which biological entities display intelligence range from the amoeba's avoidance of toxic materials to the human's acquisition of scientific knowledge. The patterns of order underlying this spectrum of activity are characterized by a wide range of complexity paralleling that of the related actions. Machine intelligence also admits of degrees. Applying the Pragmatists' general definition is primarily a matter of specifying the level of capabilities with which the investigation is concerned.

In particular, application of the general definition to AI in space applications requires interpreting "actions" to mean "