Strategic Directions in Artificial Intelligence

By Doyle, Jon; Dean, Thomas | AI Magazine, Spring 1997 | Go to article overview

Strategic Directions in Artificial Intelligence


Doyle, Jon, Dean, Thomas, AI Magazine


* This report, written for the general computing and scientific audience and for students and others interested in artificial intelligence, summarizes the major directions in artificial intelligence research, sets them in context relative to other areas of computing research, and gives a glimpse of the vision, depth, research partnerships, successes, and excitement of the field.

What Is Artificial Intelligence?

The field of artificial intelligence (AI) consists of long-standing intellectual and technological efforts addressing several interrelated scientific and practical aims:

* constructing intelligent machines, whether or not these operate in the same way as people do;

* formalizing knowledge and mechanizing reasoning, both common sense and refined expertise, in all areas of human endeavor;

* using computational models to understand the psychology and behavior of people, animals, and artificial agents; and

* making working with computers as easy and as helpful as working with skilled, cooperative, and possibly expert people.

Even considering only the first two of these aims, AI has perhaps the broadest concerns of all areas of computing research, covering investigations ranging from the natural sciences to the social, from engineering to economics, physics to psychology. Its very nature forces AI to grapple with the complexity of the natural world as well as that of the artificial systems that form the subject matter of computing studies generally. Its main theoretical questions stand as peers of the deepest and most important questions in any scientific field, and its practical impact on living promises to equal that of any known technology.

The aims of AI reflect ancient dreams of using minds and hands to create beings like ourselves. In centuries past, pursuit of these dreams gave rise to both mechanical automata and formal theories of reasoning, eventually yielding the spectacularly successful modern artificial computers that, in calculating and computing, replicate and surpass abilities that people of earlier times regarded as intellectual activities on a par with writing letters and playing good chess. Using these computers over the past four decades, modern AI has built on the best thinking in a number of areas -- especially computer systems, logic, the mathematical theory of computation, psychology, economics, control theory, and mathematical problem solving -- to construct concrete realizations of devices that

* solve intellectual problems both theoretical and practical, common and esoteric;

* control robot motions through planning, sight, touch, and self-awareness;

* interpret human language, both written and spoken; and

* learn new skills and knowledge through instruction, from experience, and by analyzing other data.

Some of these realizations have proven highly successful, others rudimentary and incomplete, but each captures recognizable and significant elements of familiar human capabilities, and provides a skeleton upon which future research may enlarge.

One can divide present-day AI research into the following primary (and overlapping) areas(2):

1. knowledge representation and articulation seeks to discover expressive and efficient forms and methods for representing information about all aspects of the world and to use these methods to create and compile explicit, formal, multipurpose catalogs of substantive knowledge;

2. learning and adaptation, which extends statistical, analytical, and scientific discovery techniques and hypothesized neurophysiological mechanisms to procedures that extract a wide range of general trends, facts, and techniques from instruction, experience, and collected data;

3. deliberation, planning, and acting, which concerns methods for making decisions, constructing plans or designs to achieve specified goals, and monitoring, interpreting, diagnosing, and correcting the performance of the plans and implementations of the designs;

4. …

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