An adaptive approach to resource allocation

Busemeyer, Jerome R.; Swenson, Kenneth N; Lazarte, Alejandro A.

doi:10.1016/0749-5978(86)90004-x

Cited by 29 publications

(36 citation statements)

References 11 publications

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“…Experimental studies by Busemeyer et al (1986) and Busemeyer and Myung (1987) on resource allocation tasks with interdependencies found strong evidence for local hill-climbing behavior in both studies. Further, participants tend to select a similar direction in allocating resources if performance increased, while failure induced search in a new direction.…”

Section: Behavioral Plausibility Of Nk Models Downloaded By [Mcmastermentioning

confidence: 92%

Modelling Bounded Rationality in Organizations: Progress and Prospects

Puranam

Stieglitz²,

Osman

et al. 2015

The Academy of Management Annals

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Much of the formal modelling work in the organizational sciences relies on HerbertSimon's conception of bounded rationality, and it stakes a claim to drawing on behaviorally plausible assumptions about human behavior and action in organizations.The objectives of our review are three-fold. First, we summarize the formal literature by "model families" -classes of models sharing the same analytical structure-to highlight sharply the behavioral assumptions being made. Specifically, we discuss model families involving a) adaptation through search and learning by individual agents, b) mutual adjustment of interacting agents, and c) information aggregation in organizational decision-making. Second, we examine to what the extent these models of bounded rationality in organizations are in fact consistent with the behavioral evidence in psychology and other related fields. Finally, we discuss opportunities for further research that strengthens the links between formal modelling in organizations research, and its behavioral foundations. In particular we highlight the promise of experimental methods that translate organizational models to multiple-subject experiments in the behavioral laboratory.

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Section: Behavioral Plausibility Of Nk Models Downloaded By [Mcmastermentioning

confidence: 92%

Modelling Bounded Rationality in Organizations: Progress and Prospects

Puranam

Stieglitz²,

Osman

et al. 2015

The Academy of Management Annals

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show abstract

“…The complementarities among different elements of a fi rm's strategy (Milgrom and Roberts, 1990) result in a complex payoff landscape in which improvements in performance often come from changing multiple aspects of the strategy together. In other words, after some local adaptation to fi nd an internally consistent strategy, incremental changes in one aspect of the strategy are often not conducive to performance gains, so that the fi rm rests on a local peak of a rugged payoff landscape (Busemeyer et al, 1986;Levinthal, 1997).…”

Section: Introductionmentioning

confidence: 99%

Effects of feedback delay on learning

Rahmandad

Repenning²,

Sterman³

2009

System Dynamics Review

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Understanding barriers to organizational learning is central to understanding fi rm performance. We investigate the role of time delays between taking an action and observing the results in impeding learning. These delays, ubiquitous in real-world settings, are relevant to tradeoffs between long term and short term. We build four learning heuristics, with different levels of complexity and rationality, and analyze their performance in a simple resource allocation task. All reliably converge to the optimal solution when there are no/short delays, and when those delays are correctly assessed. However, learning is slowed signifi cantly when decision makers err in assessing the length of the delay. In many cases, the decision maker never fi nds the optimal solution, wandering in the action space or converging to a suboptimal allocation. Results are robust to the organization's level of rationality. The proposed heuristics can be applied to a range of problems for modeling learning from experience in the presence of delays.

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“…In such cases, gradient descent learning algorithms predict that any trajectory passing through a local minimum will become trapped there, and asymptotic accuracy will, therefore, be suboptimal (White, 1989). In resource allocation tasks, it has been shown that observers are susceptible to local minima, in that information is sometimes combined in a manner that produces suboptimal performance even if the optimal performance criterion is known (Busemeyer et al, 1986). The use of the dynamical trajectory paradigm presented here could provide an extension of this research to category learning.…”

Section: Discussionmentioning

confidence: 99%

“…At the extreme, these models predict no further changes in w once w ϭ w*, because the probability-oferror surface is flat at w ϭ w* (since w* contains the coordinates of the minimum of the probability-of-error surface). In fact, empirical evidence for such decreases has been reported (Busemeyer, Swenson, & Lazarte, 1986). Even so, many category-learning models that incorporate gradient descent include an additional assumption that this decrease is even more severe than predicted by standard gradient descent.…”

Section: Dynamical Trajectoriesmentioning

confidence: 99%

Dynamical trajectories in category learning

Ell

Ashby

2004

Perception & Psychophysics

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Category learning has traditionally been studied by examining how percentage correct changes with experience (i.e., in the form of learning curves). An alternative and more powerful approach is to examine dynamical learning trajectories-that is, to examine how the parameters that describe the current state of the model change with experience. We describe results from a new experimental paradigm in which empirical-learning trajectories are directly observable. In these experiments, participants learned two categories of spatial position, and they were constrained to identify and use a linear decision bound on every trial. The dependent variables of principal interest were the slope and the intercept of the bound used on each trial. Data from two experiments supported the following conclusions.(1) Gradient descent provided a poor description of the empirical trajectories. (2) The magnitude of changes in decision strategy decreased with experience at a rate that was faster than that predicted by gradient descent. (3) Learning curves suffered from substantial identifiability problems.

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An adaptive approach to resource allocation

Cited by 29 publications

References 11 publications

Modelling Bounded Rationality in Organizations: Progress and Prospects

Modelling Bounded Rationality in Organizations: Progress and Prospects

Effects of feedback delay on learning

Dynamical trajectories in category learning

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