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 rather than by performing computational actions in the head alone. We have found that some translations and rotations are best understood as using 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 ñ actions performed to bring one physically closer to a goal - from epistemic actions - actions performed to uncover information 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 describe many such actions that are actually taken by players that are far from superfluous, and that play valuable roles 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 one category of epistemic action can be incorporated into theories of action more generally. (shrink)

Cognitive organisms have three rather different techniques for intelligently regulating their intake of environmental information. In order of the time needed to uncover information they are: 1. control of attention: within an image produced by a given sensor certain elements can be selected for additional processing; 2. control of gaze: the orientation and resolution (center of foveation) of the sensor can be regulated to create a new image; 3. control of activity: certain non-perceptual actions can be performed to increase the (...) probability of unearthing salient information that currently is unavailable, hard to detect, or hard to compute. (shrink)

The target article makes a compelling case for the idea that agents rely on the world for external memory in fast-paced perceptual tasks. As I argue, however, agents also rely on the external environment for computational hardware that helps to keep cognitive computations tractable. Hence the external world provides not only memory for computations involving perceptual system actions, but it provides domain-level actions that figure in cognitive computations as well.