Statement of Bruce H. Simon Before the Commission on the Future of Worker-Management Relations

Testimony_Simon_022494.pdf: 204 downloads, before Oct. 1, 2020

Risk and return of publicly held versus privately owned banks

The author divides bank holding companies (BHCs) into four size classes, then categorizes each class according to public or private ownership. He compares the performance and risk across bank size classes between 1986 and 2000 and in five-year windows therein. For the largest BHCs, returns on assets and operating costs do not depend on ownership, but for the smaller BHCs, returns on assets are lower and operating costs are higher for those that are publicly owned. Small public BHCs also hold more capital than do small private ones.Corporate governance ; Bank holding companies ; Bank stocks ; Bank management

Recall of rapidly presented random chess positions is a function of skill.

A widely cited result asserts that experts’ superiority over novices in recalling meaningful material from their domain of expertise vanishes when random material is used. A review of recent chess experiments where random positions served as control material (presentation time between 3 and 10 seconds) shows, however, that strong players generally maintain some superiority over weak players even with random positions, although the relative difference between skill levels is much smaller than with game positions. The implications of this finding for expertise in chess are discussed and the question of the recall of random material in other domains is raised

Five seconds or sixty? Presentation time in expert memory

The template theory presented in Gobet and Simon (1996a, 1998) is based on the EPAM theory (Feigenbaum & Simon, 1984; Richman et al., 1995), including the numerical parameters that have been estimated in tests of the latter; and it therefore offers precise predictions for the timing of cognitive processes during the presentation and recall of chess positions. This paper describes the behavior of CHREST, a computer implementation of the template theory, in a task when the presentation time is systematically varied from one second to sixty seconds, on the recall of both game and random positions, and compares the model to human data. As predicted by the model, strong players are better than weak players with both types of positions. Their superiority with random positions is especially clear with long presentation times, but is also present after brief presentation times, although smaller in absolute value. CHREST accounts for the data, both qualitatively and quantitatively. Strong players’ superiority with random positions is explained by the large number of chunks they hold in LTM. Strong players’ high recall percentage with short presentation times is explained by the presence of templates, a special class of chunks. The model is compared to other theories of chess skill, which either cannot account for the superiority of Masters with random positions (models based on high-level descriptions and on levels of processing) or predict too strong a performance of Masters with random positions (long-term working memory)

Robust estimation of risks from small samples

Data-driven risk analysis involves the inference of probability distributions from measured or simulated data. In the case of a highly reliable system, such as the electricity grid, the amount of relevant data is often exceedingly limited, but the impact of estimation errors may be very large. This paper presents a robust nonparametric Bayesian method to infer possible underlying distributions. The method obtains rigorous error bounds even for small samples taken from ill-behaved distributions. The approach taken has a natural interpretation in terms of the intervals between ordered observations, where allocation of probability mass across intervals is well-specified, but the location of that mass within each interval is unconstrained. This formulation gives rise to a straightforward computational resampling method: Bayesian Interval Sampling. In a comparison with common alternative approaches, it is shown to satisfy strict error bounds even for ill-behaved distributions.Comment: 13 pages, 3 figures; supplementary information provided. A revised version of this manuscript has been accepted for publication in Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Science

Recall of random and distorted positions: Implications for the theory of expertise.

This paper explores the question, important to the theory of expert performance, of the nature and number of chunks that chess experts hold in memory. It examines how memory contents determine players' abilities to reconstruct (a) positions from games, (b) positions distorted in various ways and (c) and random positions. Comparison of a computer simulation with a human experiment supports the usual estimate that chess Masters store some 50,000 chunks in memory. The observed impairment of recall when positions are modified by mirror image reflection, implies that each chunk represents a specific pattern of pieces in a specific location. A good account of the results of the experiments is given by the template theory proposed by Gobet and Simon (in press) as an extension of Chase and Simon's (1973a) initial chunking proposal, and in agreement with other recent proposals for modification of the chunking theory (Richman, Staszewski & Simon, 1995) as applied to various recall tasks

The Roles of recognition processes and look-ahead search in time-constrained expert problem solving: Evidence from grandmaster level chess.

Chess has long served as an important standard task environment for research on human memory and problem-solving abilities and processes. In this paper, we report evidence on the relative importance of recognition processes and planning (look-ahead) processes in very high level expert performance in chess. The data show that the rated skill of a top-level grandmaster is only slightly lower when he is playing simultaneously against a half dozen grandmaster opponents than under tournament conditions that allow much more time for each move. As simultaneous play allows little time for look-ahead processes, the data indicate that recognition, based on superior chess knowledge, plays a much larger part in high-level skill in this task than does planning by looking ahead