Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Methods of Medium Optimization01:28

Methods of Medium Optimization

52
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
52
Optimization Problems01:26

Optimization Problems

184
Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
184
Optimal Foraging00:48

Optimal Foraging

14.2K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
14.2K
Energy Budgets00:51

Energy Budgets

11.1K
Organisms must balance energy intake with the energy required for growth, maintenance and reproduction. These trade-offs result in a variety of survivorship and reproductive strategies, including semelparity and iteroparity. Semelparous species, like annual plants, have only one reproductive episode in their lifetimes and consequently have short lifespans. Iteroparous species, by contrast, have many reproductive events during their lifetimes but have relatively few offspring. These two...
11.1K
The Availability Heuristic01:08

The Availability Heuristic

7.3K
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
7.3K
Heuristics01:21

Heuristics

872
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
872

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Artificial transneurons emulate neuronal activity in different areas of brain cortex.

Nature communications·2025
Same author

Toward a Database of Intracranial Electrophysiology during Natural Language Presentation.

Language, cognition and neuroscience·2022
Same author

Spatially distributed computation in cortical circuits.

Science advances·2022
Same author

Distraction "Hangover": Characterization of the Delayed Return to Baseline Driving Risk After Distracting Behaviors.

Human factors·2021
Same author

Proprioceptive recalibration following implicit visuomotor adaptation is preserved in Parkinson's disease.

Experimental brain research·2021
Same author

A Statistical Growth Property of Plant Root Architectures.

Plant phenomics (Washington, D.C.)·2020
Same journal

Another 10 years of PLOS Computational Biology: A data-driven reflection on trends in genomics research.

PLoS computational biology·2026
Same journal

Mobility data resolution needed to inform predictive models of spatial epidemic spread from mobile phone data.

PLoS computational biology·2026
Same journal

DeepMethylation: A deep learning framework for tissue-specific DNA methylation prediction and functional variant annotation.

PLoS computational biology·2026
Same journal

Redefining and estimating the early-phase reproduction ratio for epidemic outbreaks in spatially structured populations.

PLoS computational biology·2026
Same journal

Optimized phenotype definitions boost GWAS power.

PLoS computational biology·2026
Same journal

Detection, communication, and individual identification with deep audio embeddings: A case study with North Atlantic right whales.

PLoS computational biology·2026
See all related articles

Related Experiment Video

Updated: Apr 3, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.6K

Prospective Optimization with Limited Resources.

Joseph Snider1, Dongpyo Lee1, Howard Poizner2

  • 1Institute for Neural Computation, University of California at San Diego, La Jolla, California, United States of America.

Plos Computational Biology
|September 15, 2015
PubMed
Summary
This summary is machine-generated.

Humans navigate future uncertainty by balancing computational depth and recalculation frequency. They prioritize precise reward assessment over simple heuristics when making decisions in dynamic environments.

Related Experiment Videos

Last Updated: Apr 3, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.6K

Area of Science:

  • Cognitive Science
  • Decision Science
  • Behavioral Economics

Background:

  • Human decision-making is inherently limited by uncertainty regarding future events and the consequences of actions.
  • Foreseeing outcomes is challenging due to unpredictable external factors and the complexity of internal cognitive processes.

Purpose of the Study:

  • To investigate human strategies for action selection under conditions of extrinsic and intrinsic uncertainty.
  • To analyze how individuals manage computational resources when faced with an exponentially expanding set of future prospects.

Main Methods:

  • A visual task on a touchscreen simulating a dynamic environment with branching reward opportunities.
  • Participants navigated a grid, making sequential choices to maximize cumulative reward, with each step influencing future options.
  • Human behavior was compared against ideal actor models to identify decision-making strategies, specifically computational depth and recalculation period.

Main Results:

  • Humans exhibit a trade-off between the depth of their computation (how far they look ahead) and their recalculation period (how often they update future assessments).
  • This trade-off aligns with a resource-limited, exhaustive search strategy up to a finite depth.
  • Participants demonstrated sensitivity to fine reward distinctions and avoided simplistic heuristics like always choosing the largest rewards.

Conclusions:

  • Human decision-making under uncertainty involves a strategic allocation of cognitive resources between planning depth and adaptability.
  • Precision in evaluating future rewards is prioritized over the adoption of easily computable, but potentially suboptimal, heuristics.
  • The findings offer insights into the cognitive mechanisms underlying complex, real-world decision-making processes.