Act First, Think Later: The Presence and Absence of Inferential Planning in Problem Solving

By Ormerod, Thomas C.; MacGregor, James N. et al. | Memory & Cognition, October 2013 | Go to article overview

Act First, Think Later: The Presence and Absence of Inferential Planning in Problem Solving


Ormerod, Thomas C., MacGregor, James N., Chronicle, Edward P., Dewald, Andrew D., Chu, Yun, Memory & Cognition


Abstract Planning is fundamental to successful problem solving, yet individuals sometimes fail to plan even one step ahead when it lies within their competence to do so. In this article, we report two experiments in which we explored variants of a ball-weighing puzzle, a problem that has only two steps, yet nonetheless yields performance consistent with a failure to plan. The results fit a computational model in which a solver's attempts are determined by two heuristics: maximization of the apparent progress made toward the problem goal and minimization of the problem space in which attempts are sought. The effectiveness of these heuristics was determined by lookahead, defined operationally as the number of steps evaluated in a planned move. Where move outcomes cannot be visualized but must be inferred, planning is constrained to the point where some individuals apply zero lookahead, which with n-ball problems yields seemingly irrational unequal weighs. Applying general-purpose heuristics with or without lookahead accounts for a range of rational and irrational phenomena found with insight and noninsight problems.

Keywords Planning . Problem-solving . Insight . Planning failures . Look ahead

Introduction

Planning is generally regarded as a prerequisite for successful cognitive performance (Hayes-Roth & Hayes-Roth, 1979; Morris & Ward, 2005; Newell & Simon, 1972; O'Hara & Payne 1998) and differentiates humans from many other species (Tomasello, Carpenter, Call, Behne, & Moll, 2005). By looking ahead mentally from a current state in order to anticipate a new state, an individual can evaluate the likely success of a move sequence before its execution. Such planning can reduce effort and avoid potentially costly errors or irreversible commitments. As implemented by VanLehn (1989)intermsoflookahead (the number of steps/moves that an individual plans ahead mentally), planning has been shown to be an important moderator of performance in models of problem solving (e.g., Jones, 2003; MacGregor, Ormerod, & Chronicle, 2001).

While failures of planning have been implicated in a number of neurodegenerative diseases (e.g., Stuss & Alexander, 2007), healthy individuals who possess the necessary cognitive resources (e.g., working memory capacity, relevant domain knowledge, reasoning skills) may also fail to plan when it is in their interests to do so. Some major disasters may be attributed to failures of planning (e.g., Fukushima: Cooper, 2011). Mundane examples of planning absence arise in everyday life (e.g., failing to warm the oven in advance of starting to cook a meal). A failure to plan can give rise to behaviors that in retrospect appear irrational, like sitting on a branch of a tree while you saw it off.

Over the last 40 years, evidence has amassed that human performance deviates from what is normatively rational (Kahneman & Tversky, 1972, 2000), and planning failures, in the form of impulsivity, have been implicated as a root cause (Kahneman, 2003). However, some have argued that what may appear irrational from one perspective may be rational from another (Gigerenzer & Gaissmaier, 2011; Gigerenzer & Goldstein, 1996), one example being the information-gain explanation of choices in the Wason selection task. Under this criterion, it is argued, the common "wrong" responses become rational (Oaksford & Chater, 1996, 2003). Recently, an information-gain explanation has been extended to choices in a weighing task, where the goal was to identify an underweight member in a set of otherwise identical objects (Wakebe, Sato, Watamura, & Takano, 2012). The example recalled a different weighing task (Simmel, 1953), where apparently irrational choices did not appear to be readily explained by information gain. Here we propose and test an explanation of the behavior using a model of problem solving that accounts for the frequent "irrational" response, frequent "rational" but incorrect responses, and the correct response. …

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