Enabling spontaneous analogy through heuristic change.

Despite analogy playing a central role in theories of problem solving, learning and education, demonstrations of spontaneous analogical transfer are rare. Here, we present a theory of heuristic change for spontaneous analogical transfer, tested in four experiments that manipulated the experience of failure to solve a source problem prior to attempting a target problem. In Experiment 1, participants solved more source problems that contained an additional financial constraint designed to signal the inappropriateness of moves that maximized progress towards the goal.

Effects of cluster location and cluster distribution on performance on the traveling salesman problem.

Research on human performance in solving traveling salesman problems typically uses point sets as stimuli, and most models have proposed a processing stage at which stimulus dots are clustered. However, few empirical studies have investigated the effects of clustering on performance. In one recent study, researchers compared the effects of clustered, random, and regular stimuli, and concluded that clustering facilitates performance (Dry, Preiss, & Wagemans, 2012).

Act first, think later: the presence and absence of inferential planning in problem solving.

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.

Rebus puzzles as insight problems.

Research on insight-the phenomenon of suddenly solving an apparently intransigent problem--has been hampered because stimulus problems have been few, ad hoc, heterogeneous, and difficult to solve. Responding to the need for a larger pool of problems of a similar type and of varying level of difficulty, we report an experiment testing the validity of rebuses as insight problems. A rebus combines verbal and visual clues to a common phrase, such as PAINS ("growing pains").

It looks easy! Heuristics for combinatorial optimization problems.

Human performance on instances of computationally intractable optimization problems, such as the travelling salesperson problem (TSP), can be excellent. We have proposed a boundary-following heuristic to account for this finding. We report three experiments with TSPs where the capacity to employ this heuristic was varied.

Convex hull or crossing avoidance? Solution heuristics in the traveling salesperson problem.

Untrained adults appear to have access to cognitive processes that allow them to perform well in the Euclidean version of the traveling salesperson problem (E-TSP). They do so despite the famous computational intractability of the problem, which stems from its combinatorial complexity. A current hypothesis is the humans' good performance is based on following a strategy of connecting boundary points in order (the convex hull hypothesis).

What makes an insight problem? The roles of heuristics, goal conception, and solution recoding in knowledge-lean problems.

Four experiments investigated transformation problems with insight characteristics. In Experiment 1, performance on a version of the 6-coin problem that had a concrete and visualizable solution followed a hill-climbing heuristic. Experiment 2 demonstrated that the difficulty of a version of the problem that potentially required insight for solution stems from the same hill-climbing heuristic, which creates an implicit conceptual block.

Dynamics and constraints in insight problem solving.

This article reports 2 experiments that investigated performance on a novel insight problem, the 8-coin problem. The authors hypothesized that participants would make certain initial moves (strategic moves) that seemed to make progress according to the problem instructions but that nonetheless would guarantee failure to solve the problem. Experiment 1 manipulated the starting state of the problem and showed that overall solution rates were lower when such strategic moves were available.