Decision-making studies: I. The trade-off of variables in decision making.

1960 ◽  
Author(s):  
J. R. Hayes ◽  
Elizabeth C. Smith
Keyword(s):  
Decision Making ◽  
Trade Off

Making the most of individual differences in joint decisions

2018 ◽  
Author(s):  
Bahador Bahrami
Keyword(s):  
Decision Making ◽  
Direct Evidence ◽  
Cross Cultural ◽  
Collective Decision Making ◽  
Wisdom Of Crowds ◽  
Trade Off ◽  
Adaptive Value ◽  
Joint Decisions ◽  
Cultural Data ◽  
Better Than

Evidence for and against the idea that “two heads are better than one” is abundant. This chapter considers the contextual conditions and social norms that predict madness or wisdom of crowds to identify the adaptive value of collective decision-making beyond increased accuracy. Similarity of competence among members of a collective impacts collective accuracy, but interacting individuals often seem to operate under the assumption that they are equally competent even when direct evidence suggest the opposite and dyadic performance suffers. Cross-cultural data from Iran, China, and Denmark support this assumption of similarity (i.e., equality bias) as a sensible heuristic that works most of the time and simplifies social interaction. Crowds often trade off accuracy for other collective benefits such as diffusion of responsibility and reduction of regret. Consequently, two heads are sometimes better than one, but no-one holds the collective accountable, not even for the most disastrous of outcomes.

Novel Multi-objective Decision-Making and Trade-Off Approach for Selecting Optimal Machining Parameters of Inconel-800 Superalloy

2020 ◽  
Vol 45 (7) ◽  
pp. 5833-5847 ◽  
Author(s):  
Syed Abou Iltaf Hussain ◽  
Binayak Sen ◽  
Archisman Das Gupta ◽  
Uttam Kumar Mandal
Keyword(s):  
Decision Making ◽  
Machining Parameters ◽  
Trade Off ◽  
Multi Objective ◽  
Inconel 800

Using trade-off information in decision-making algorithms

2000 ◽  
Vol 27 (2) ◽  
pp. 161-182 ◽  
Author(s):  
Ignacy Kaliszewski
Keyword(s):  
Decision Making ◽  
Trade Off

scholarly journals Neural signatures of value comparison in human cingulate cortex during decisions requiring an effort-reward trade-off

2016 ◽  
Author(s):  
Miriam C Klein-Flügge ◽  
Steven W Kennerley ◽  
Karl Friston ◽  
Sven Bestmann
Keyword(s):  
Decision Making ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Optimal Decision ◽  
Trade Off ◽  
Trade Offs ◽  
Caudal Portion ◽  
Neural Signature ◽  
The Difference ◽  
Neural Signatures

AbstractIntegrating costs and benefits is crucial for optimal decision-making. While much is known about decisions that involve outcome-related costs (e.g., delay, risk), many of our choices are attached to actions and require an evaluation of the associated motor costs. Yet how the brain incorporates motor costs into choices remains largely unclear. We used human functional magnetic resonance imaging during choices involving monetary reward and physical effort to identify brain regions that serve as a choice comparator for effort-reward trade-offs. By independently varying both options' effort and reward levels, we were able to identify the neural signature of a comparator mechanism. A network involving supplementary motor area (SMA) and the caudal portion of dorsal anterior cingulate cortex (dACC) encoded the difference in reward (positively) and effort levels (negatively) between chosen and unchosen choice options. We next modelled effort-discounted subjective values using a novel behavioural model. This revealed that the same network of regions involving dACC and SMA encoded the difference between the chosen and unchosen options' subjective values, and that activity was best described using a concave model of effort-discounting. In addition, this signal reflected how precisely value determined participants' choices. By contrast, separate signals in SMA and ventro-medial PFC (vmPFC) correlated with participants' tendency to avoid effort and seek reward, respectively. This suggests that the critical neural signature of decision-making for choices involving motor costs is found in human cingulate cortex and not vmPFC as typically reported for outcome-based choice. Furthermore, distinct frontal circuits ‘drive’ behaviour towards reward-maximization and effort-minimization.Significance StatementThe neural processes that govern the trade-off between expected benefits and motor costs remain largely unknown. This is striking because energetic requirements play an integral role in our day-to-day choices and instrumental behaviour, and a diminished willingness to exert effort is a characteristic feature of a range of neurological disorders. We use a new behavioural characterization of how humans trade-off reward-maximization with effort-minimization to examine the neural signatures that underpin such choices, using BOLD MRI neuroimaging data. We find the critical neural signature of decision-making, a signal that reflects the comparison of value between choice options, in human cingulate cortex, whereas two distinct brain circuits ‘drive’ behaviour towards reward-maximization or effort-minimization.

scholarly journals Lapses in perceptual decisions reflect exploration

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Sashank Pisupati ◽  
Lital Chartarifsky-Lynn ◽  
Anup Khanal ◽  
Anne K Churchland
Keyword(s):  
Decision Making ◽  
Motor Cortex ◽  
Reward Magnitude ◽  
Decision Makers ◽  
Decision Task ◽  
Trade Off ◽  
Strategic Trade ◽  
Evidence Strength ◽  
Constant Rate ◽  
Brain States

Perceptual decision-makers often display a constant rate of errors independent of evidence strength. These 'lapses' are treated as a nuisance arising from noise tangential to the decision, e.g. inattention or motor errors. Here, we use a multisensory decision task in rats to demonstrate that these explanations cannot account for lapses' stimulus dependence. We propose a novel explanation: lapses reflect a strategic trade-off between exploiting known rewarding actions and exploring uncertain ones. We tested this model's predictions by selectively manipulating one action's reward magnitude or probability. As uniquely predicted by this model, changes were restricted to lapses associated with that action. Finally, we show that lapses are a powerful tool for assigning decision-related computations to neural structures based on disruption experiments (here, posterior striatum and secondary motor cortex). These results suggest that lapses reflect an integral component of decision-making and are informative about action values in normal and disrupted brain states.

From Monetary to Nonmonetary Mechanism Design via Artificial Currencies

2021 ◽  
Author(s):  
Artur Gorokh ◽  
Siddhartha Banerjee ◽  
Krishnamurthy Iyer
Keyword(s):  
Decision Making ◽  
Mechanism Design ◽  
Real World ◽  
Price Of Anarchy ◽  
Black Box ◽  
Trade Off ◽  
Two Agents ◽  
Over Time ◽  
Artificial Currency

Nonmonetary mechanisms for repeated allocation and decision making are gaining widespread use in many real-world settings. Our aim in this work is to study the performance and incentive properties of simple mechanisms based on artificial currencies in such settings. To this end, we make the following contributions: For a general allocation setting, we provide two black-box approaches to convert any one-shot monetary mechanism to a dynamic nonmonetary mechanism using an artificial currency that simultaneously guarantees vanishing gains from nontruthful reporting over time and vanishing losses in performance. The two mechanisms trade off between their applicability and their computational and informational requirements. Furthermore, for settings with two agents, we show that a particular artificial currency mechanism also results in a vanishing price of anarchy.

The Aggregation–Learning Trade-off

2021 ◽  
Author(s):  
Henning Piezunka ◽  
Vikas A. Aggarwal ◽  
Hart E. Posen
Keyword(s):  
Decision Making ◽  
Crucial Role ◽  
Management Practice ◽  
Learning By Doing ◽  
Top Management Teams ◽  
Corporate Boards ◽  
Organizational Decision Making ◽  
Trade Off ◽  
Collective Wisdom ◽  
Alternative Decision

Organizational decision making that leverages the collective wisdom and knowledge of multiple individuals is ubiquitous in management practice, occurring in settings such as top management teams, corporate boards, and the teams and groups that pervade modern organizations. Decision-making structures employed by organizations shape the effectiveness of knowledge aggregation. We argue that decision-making structures play a second crucial role in that they shape the learning of individuals that participate in organizational decision making. In organizational decision making, individuals do not engage in learning by doing but, rather, in what we call learning by participating, which is distinct in that individuals learn by receiving feedback not on their own choices but, rather, on the choice made by the organization. We examine how learning by participating influences the efficacy of aggregation and learning across alternative decision-making structures and group sizes. Our central insight is that learning by participating leads to an aggregation–learning trade-off in which structures that are effective in aggregating information can be ineffective in fostering individual learning. We discuss implications for research on organizations in the areas of learning, microfoundations, teams, and crowds.

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