Abstract. The Frame-Stewart algorithm for the 4-peg variant of the Tower of Hanoi, introduced in 1941, partitions disks into intermediate towers before moving the remaining disks to their destination. Algo-rithms that partition the disks have not been proven to be optimal, although they have been

’ ’ or ‘‘executive’ ’ tasks. One hun-dred thirty-seven college students performed a set of relatively simple experimental tasks that are considered to predominantly tap each target executive function as well as a set of frequently used executive tasks: the Wisconsin Card Sorting Test (WCST), Tower of Hanoi (TOH

The central proposal of this article is that verbal reports are data. Accounting for verbal reports, as for other kinds of data, requires explication of the mech-anisms by which the reports are generated, and the ways in which they are sensitive to experimental factors (instructions, tasks, etc.). Within the theoret-ical framework of human information processing, we discuss different types of processes underlying verbalization and present a model of how subjects, in re-sponse to an instruction to think aloud, verbalize information that they are attending to in short-term memory (STM). Verbalizing information is shown to affect cognitive processes only if the instructions require verbalization of information that would not otherwise be attended to. From an analysis of what would be in STM at the time of report, the model predicts what can reliably be reported. The inaccurate reports found by other research are shown to result from requesting information that was never directly heeded, thus forcing subjects to infer rather than remember their mental processes. After a long period of time during which stimulus-response relations were at the focus of attention, research in psychology is now seeking to understand in detail the mecha-nisms and internal structure of cognitive pro-cesses that produce these relations. In the limiting case, we would like to have process models so explicit that they could actually produce the predicted behavior from the in-formation in the stimulus.

It has recently been shown that local search issurprisingly good at nding satisfying assignments for certain computationally hard classes of CNF formulas. The performance of basic local search methods can be further enhanced by introducing mechanisms for escaping from local minima in the search space. We will compare three such mechanisms: simulated annealing, random noise, and a strategy called \mixed random walk". We show that mixed random walk is the superior strategy. Wealso present results demonstrating the e ectiveness of local search withwalk for solving circuit synthesis and circuit diagnosis problems. Finally, wedemonstrate that mixed random walk improves upon the best known methods for solving MAX-SAT problems.

Experimental economists are leaving the reservation. They are recruiting subjects in the field rather than in the classroom, using field goods rather than induced valuations, and using field context rather than abstract terminology in instructions. We argue that there is something methodologically fundamental behind this trend. Field experiments differ from laboratory experiments in many ways. Although it is tempting to view field experiments as simply less controlled variants of laboratory experiments, we argue that to do so would be to seriously mischaracterize them. What passes for “control ” in laboratory experiments might in fact be precisely the opposite if it is artificial to the subject or context of the task. We propose six factors that can be used to determine the field context of an experiment: the nature of the subject pool, the nature of the information that the subjects bring to the task, the nature of the commodity, the nature of the task or trading rules applied, the nature

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It has recently been shown that local search is surprisingly good at finding satisfying assignments for certain classes of CNF formulas [24]. In this paper we demonstrate that the power of local search for satisfiability testing can be further enhanced by employinga new strategy, called "mixed random walk", for escaping from local minima. We present experimental results showing how this strategy allows us to handle formulas that are substantially larger than those that can be solved with basic local search. We also present a detailed comparison of our random walk strategy with simulated annealing. Our results show that mixed random walk is the superior strategy on several classes of computationally difficult problem instances. Finally, we present results demonstrating the effectiveness of local search with walk for solving circuit synthesis and diagnosis problems.

to sample problems including the &quot;Monkey and Bananas &quot; puzzle and the 'Tower of Hanoi &quot; puzzle. The paper exhibits solutions to these problems obtained by QA3, a computer program bused on these theorem-proving methods. In addition, the paper shows how QA3 can write simple

pattern databases. Here we partition the problem into disjoint subproblems for each state of the search dynamically. We discuss the pros and cons of each of these methods and apply both methods to three different problem domains: the sliding-tile puzzles, the 4-peg Towers of Hanoi problem, and finding

This article provides one example of a method of analyzing qualitative data in an objective and quantifiable way. Although the application of the method is illustrated in the context of verbal data such as explanations, interviews, problem-solving protocols, and retrospective reports, in principle, the mechanics of the method can be adapted for coding other types of qualitative data such as gestures and videotapes. The mechanics of the method we outlined in 8 concrete step. Although verbal analyses can be used for many purposes, the main goal of the analyses discussed here is to formulate an understanding of the representation of the knowledge used in cognitive performances and how that representation changes with learning This can be contrasted with another method or analyzing verbal protocols, the goal of which is to validate the cognitive processes of human performance, often as embodied in a computational model