Decomposable Probability-of-Success Metrics in Algorithmic Search

Abstract. The current study investigates the behavior of task-specific, current achievement motivation (CAM: interest in the task, probability of success, perceived challenge, and fear of failure) across a variety of reasoning tasks featuring verbal, numerical, and figural content. CAM is conceptualized as a state-like variable, and in order to assess the relative stability of the four CAM variables across different tasks, latent state trait analyses are conducted. The major findings indicate that the degree of challenge a test taker experiences and the fear of failing a given task appear to be relatively stable regardless of the specific task utilized, whereas interest and probability of success are more directly influenced by task-specific characteristics and demands. Furthermore, task performance is related to task-specific interest and probability of success. We discuss the implications and benefits of these results with regard to the use of cognitive ability tests in general. Importantly, taking motivational differences between test takers into account appears to offer valuable information which helps to explain differences in task performance.

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Can Preparing for Failure Reduce the Probability of Success?

PsycEXTRA Dataset ◽

10.1037/e573552014-071 ◽

2014 ◽

Author(s):

Jihae Shin ◽

Katherine L. Milkman

Keyword(s):

Probability Of Success

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The role of probability of success estimates in the sunk cost effect

PsycEXTRA Dataset ◽

10.1037/e683282011-061 ◽

1997 ◽

Author(s):

Hal R. Arkes ◽

Laura Hutzel

Keyword(s):

Sunk Cost ◽

Sunk Cost Effect ◽

Probability Of Success ◽

Cost Effect

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"Relative Self-Evaluation," anxiety, probability of success, and Sullivan's theory of the interpersonal nature of personality

10.31274/rtd-180816-3370 ◽

1974 ◽

Author(s):

Rebecca O. Johnson

Keyword(s):

Self Evaluation ◽

Probability Of Success ◽

Evaluation Anxiety

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The Ethics of Unwinnable War

10.1093/oso/9780198801825.003.0008 ◽

2017 ◽

Author(s):

Dominic Tierney

Keyword(s):

High Probability ◽

Just War ◽

Just War Theory ◽

Moral Dilemmas ◽

Probability Of Success ◽

Military Campaigns ◽

Military Campaign

According to just war theory, military campaigns should only be fought as a last resort, with the goal of correcting a grave evil, and where there is a high probability of success. But what happens when a military campaign unravels and becomes unwinnable? How can a leader reconcile just war theory with the need to extricate the country from a quagmire? In recent decades, US presidents have repeatedly faced such moral dilemmas, as campaigns in Korea, Vietnam, Afghanistan, and Iraq all became unwinnable. When victory is no longer achievable, leaders should dial down the goals of the war, resist the pressure to embrace barbarism, negotiate with the adversary, and seek the best possible peace from the range of plausible alternatives.

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Cost-effectiveness Analysis of Submandibular Gland Preservation With Sialendoscopy for the Management of Sialolithiasis

Otolaryngology ◽

10.1177/01945998211026847 ◽

2021 ◽

pp. 019459982110268

Author(s):

Joseph R. Acevedo ◽

Ashley C. Hsu ◽

Jeffrey C. Yu ◽

Dale H. Rice ◽

Daniel I. Kwon ◽

...

Keyword(s):

Cost Effectiveness ◽

Submandibular Gland ◽

Average Cost ◽

Cost Effective ◽

Cost Effectiveness Analysis ◽

Effectiveness Analysis ◽

Life Years ◽

Probability Of Success ◽

Markov Decision Model ◽

The Cost

Objective To compare the cost-effectiveness of sialendoscopy with gland excision for the management of submandibular gland sialolithiasis. Study Design Cost-effectiveness analysis. Setting Outpatient surgery centers. Methods A Markov decision model compared the cost-effectiveness of sialendoscopy versus gland excision for managing submandibular gland sialolithiasis. Surgical outcome probabilities were found in the primary literature. The quality of life of patients was represented by health utilities, and costs were estimated from a third-party payer’s perspective. The effectiveness of each intervention was measured in quality-adjusted life-years (QALYs). The incremental costs and effectiveness of each intervention were compared, and a willingness-to-pay ratio of $150,000 per QALY was considered cost-effective. One-way, multivariate, and probabilistic sensitivity analyses were performed to challenge model conclusions. Results Over 10 years, sialendoscopy yielded 9.00 QALYs at an average cost of $8306, while gland excision produced 8.94 QALYs at an average cost of $6103. The ICER for sialendoscopy was $36,717 per QALY gained, making sialendoscopy cost-effective by our best estimates. The model was sensitive to the probability of success and the cost of sialendoscopy. Sialendoscopy must meet a probability-of-success threshold of 0.61 (61%) and cost ≤$11,996 to remain cost-effective. A Monte Carlo simulation revealed sialendoscopy to be cost-effective 60% of the time. Conclusion Sialendoscopy appears to be a cost-effective management strategy for sialolithiasis of the submandibular gland when certain thresholds are maintained. Further studies elucidating the clinical factors that determine successful sialendoscopy may be aided by these thresholds as well as future comparisons of novel technology.

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Hybrid Verification Technique for Decision-Making of Self-Driving Vehicles

Journal of Sensor and Actuator Networks ◽

10.3390/jsan10030042 ◽

2021 ◽

Vol 10 (3) ◽

pp. 42

Author(s):

Mohammed Al-Nuaimi ◽

Sapto Wibowo ◽

Hongyang Qu ◽

Jonathan Aitken ◽

Sandor Veres

Keyword(s):

Decision Making ◽

Autonomous Vehicle ◽

Autonomous Driving ◽

Practical Implementation ◽

Model Checker ◽

Multi Agent Systems ◽

Time Operation ◽

Bdi Agent ◽

Perception System ◽

Probability Of Success

The evolution of driving technology has recently progressed from active safety features and ADAS systems to fully sensor-guided autonomous driving. Bringing such a vehicle to market requires not only simulation and testing but formal verification to account for all possible traffic scenarios. A new verification approach, which combines the use of two well-known model checkers: model checker for multi-agent systems (MCMAS) and probabilistic model checker (PRISM), is presented for this purpose. The overall structure of our autonomous vehicle (AV) system consists of: (1) A perception system of sensors that feeds data into (2) a rational agent (RA) based on a belief–desire–intention (BDI) architecture, which uses a model of the environment and is connected to the RA for verification of decision-making, and (3) a feedback control systems for following a self-planned path. MCMAS is used to check the consistency and stability of the BDI agent logic during design-time. PRISM is used to provide the RA with the probability of success while it decides to take action during run-time operation. This allows the RA to select movements of the highest probability of success from several generated alternatives. This framework has been tested on a new AV software platform built using the robot operating system (ROS) and virtual reality (VR) Gazebo Simulator. It also includes a parking lot scenario to test the feasibility of this approach in a realistic environment. A practical implementation of the AV system was also carried out on the experimental testbed.

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