On distinguishing epistemic from pragmatic action 论文

1994Cognitive Science引用 294
Artificial Intelligence in Games

详细信息

发表期刊/会议
Cognitive Science
发表日期
1994-12-01
发表年份
1994

关键词

Artificial Intelligence in Games

摘要

We present data and argument to show that in Tetris—a real-time, interactive video game—certain cognitive and perceptual problems are more quickly, easily, and reliably solved by performing actions in the world than by performing computational actions in the head alone. We have found that some of the translations and rotations made by players of this video game are best understood as actions that use the world to improve cognition. These actions are not used to implement a plan, or to implement a reaction; they are used to change the world in order to simplify the problem-solving task. Thus, we distinguish pragmatic actions—actions performed to bring one physically closer to a goal—from epistemic actions—actions performed to uncover informatioan that is hidden or hard to compute mentally. To illustrate the need for epistemic actions, we first develop a standard information-processing model of Tetris cognition and show that it cannot explain performance data from human players of the game—even when we relax the assumption of fully sequential processing. Standard models disregard many actions taken by players because they appear unmotivated or superfluous. However, we show that such actions are actually far from superfluous; they play a valuable role in improving human performance. We argue that traditional accounts are limited because they regard action as having a single function: to change the world. By recognizing a second function of action—an epistemic function—we can explain many of the actions that a traditional model cannot. Although our argument is supported by numerous examples specifically from Tetris, we outline how the new category of epistemic action can be incorporated into theories of action more generally.

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