Goal-Based Decision Making: An Interpersonal Model

Goal-Based Decision Making: An Interpersonal Model

Goal-Based Decision Making: An Interpersonal Model

Goal-Based Decision Making: An Interpersonal Model

Synopsis

This work presents a goal-based model of decision making in which the relative priorities of goals drive the decision process -- a psychological alternative to traditional decision analysis. Building on the work of Schank and Abelson, the author uses goals as the basis for a model of interpersonal relations which permits decisions to incorporate personal and adopted goals in a uniform manner. The theory is modelled on the VOTE computer program which simulates Congressional roll-call voting decisions.

The VOTE program expands traditional decision making and simulation models by providing not only a choice, but also a natural language explanation, in either English or French. It simulates real members of Congress voting on real bills, and producing reasonable explanations. The program is consistent with much of the descriptive political science literature on Congressional decision making and provides an explicit model of political issues, relationships, and strategies that converge in voting behavior.

In developing the VOTE program, the author draws on his own practical experience in politics from four presidential campaigns and the White House. Given the underlying psychological basis of the program, VOTE can be extended to other decision making domains different from politics. Another use for the program is to simulate business decisions such as securities analysis, as well as mundane decision making such as choosing a college or deciding whether to get a Mohawk haircut.

Excerpt

A philosophy professor was in the middle of a lecture. Suddenly, there was a brilliant flash of light, and a genie appeared at the front of the classroom.

"I will grant you one of three wishes," said the genie, addressing the professor. "You may have unlimited wealth, unlimited wisdom, or unlimited happiness."

The professor paused, and then stated, "I choose wisdom."

There was a second flash of light, after which the genie was gone. The professor stood alone at the front of the class, but with a slightly perceptible glow surrounding his head. The room was silent. Finally, a student spoke up.

"Professor, what can you tell us?"

The professor slowly turned to face the student and replied, "I should have taken the money."

Decision making is a pervasive human activity. We make scores of mundane choices every day. When faced with an important decision, we, like the philosophy professor, do not possess unlimited wisdom. Neither do computers.

In this book, we view decision making as a process, not as a mathematical formula. Artificial intelligence (AI) provides a methodology for simulating the process of decision making. There are several advantages of the Al approach.

First, an Al model must be computationally feasible. That is, we are prevented from postulating theories that require unlimited information or processing. Presumably, human decision makers must comply with this same computational constraint.

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