Academic journal article Memory & Cognition

Putting the Psychology Back into Psychological Models: Mechanistic versus Rational Approaches

Academic journal article Memory & Cognition

Putting the Psychology Back into Psychological Models: Mechanistic versus Rational Approaches

Article excerpt

Two basic approaches to explaining the nature of the mind are the rational and the mechanistic approaches. Rational analyses attempt to characterize the environment and the behavioral outcomes that humans seek to optimize, whereas mechanistic models attempt to simulate human behavior using processes and representations analogous to those used by humans. We compared these approaches with regard to their accounts of how humans learn the variability of categories. The mechanistic model departs in subtle ways from rational principles. In particular, the mechanistic model incrementally updates its estimates of category means and variances through error-driven learning, based on discrepancies between new category members and the current representation of each category. The model yields a prediction, which we verify, regarding the effects of order manipulations that the rational approach does not anticipate. Although both rational and mechanistic models can successfully postdict known findings, we suggest that psychological advances are driven primarily by consideration of process and representation and that rational accounts trail these breakthroughs.

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Two basic approaches to explaining the nature of the mind are the rational and the mechanistic approaches. Rational analyses attempt to characterize the environment and the behavioral outcomes that humans seek to optimize. The rational approach holds that people are adaptive and learn (at the individual or species level) to behave optimally given the nature of the environment (i.e., given available information or statistics). The formal product of a rational analysis is an abstract mathematical model (often Bayesian) that details the behavioral strategies that optimize some cost function, given the environment. Such models do not have recourse to how people actually process and represent information but are, instead, abstract.

Considerations of the environment and optimality also resonate with adherents of the mechanistic program, but unlike for a rational model, the main goal of a mechanistic model is to simulate human behavior by using mechanisms (i.e., analogous processes and representations) that are the same as those that support human behavior. The mechanistic program seeks to reverse engineer the human brain and peer inside the black box. The issues of primary importance to the mechanistic program are how people represent and process information.

One common criticism of mechanistic approaches is that they lead to ad hoc explanations that lack the elegance and clarity of models derived from rational analysis. To the extent that two models converge on a common set of predictions, the more transparent and mathematically motivated model should be favored. Echoing these sentiments, Anderson (1991b) stated, "All mechanistic proposals which implement the same rational prescription are the same," and "a rational theory provides a precise characterization and justification of the behavior the mechanistic theory should achieve." These views are seconded by Chater and Oaksford (1999): "The picture that emerges from this focus on mechanistic explanation is of the cognitive system as an assortment of apparently arbitrary mechanisms, subject to equally capricious limitations, with no apparent rationale or purpose."

The upshot of these statements is that mechanisms are subservient to rational accounts of thought. Perhaps in a moment of candor or euphoria, Anderson (1991b) stated that rational models render mechanistic models unnecessary: "One might take the view (and I have so argued in overenthusiastic moments; Anderson, in press) that we do not need a mechanistic theory, that a rational theory offers a more appropriate explanatory level for behavioral data" (p. 471). We believe that these general sentiments explain the rising popularity of rational accounts of cognition (for reviews, see Chater, Tenenbaum, & Yuille, 2006; Griffiths, Kemp, & Tenenbaum, 2008). …

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