Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...

Decision Making: Traditional Method

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...

Observational Learning

Observational Learning

Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning because...

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Statically Indeterminate Problem Solving

Statically Indeterminate Problem Solving

Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...

Associative Learning

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...

You might also read

Related Articles

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

Sort by

Same author

Incidence and strategies for prevention of adjustable loop suspensory fixation maldeployment in multiligament knee reconstruction.

Journal of ISAKOS : joint disorders & orthopaedic sports medicine·2026

Same author

Safe and reproducible knee posterolateral portal development using an arthroscopic inside-out technique: A technical note and retrospective case series of current technique.

Journal of ISAKOS : joint disorders & orthopaedic sports medicine·2025

Same author

Early peripheral blood gene expression predicts 90-day outcomes following subarachnoid hemorrhage.

Journal of neuroinflammation·2025

Same author

Collagenolytic <i>Enterococcus faecalis</i> induces DDR1 signaling, proliferation and altered immune infiltrate in colorectal peritoneal metastases.

Surgery open science·2025

Same author

Complement Factor I Deficiency With Acute Hemorrhagic Leukoencephalitis and Longitudinally Extensive Transverse Myelitis: A Case Report.

Neurology(R) neuroimmunology & neuroinflammation·2025

Same author

Participatory evaluation of a transdisciplinary behavioral health research center.

Evaluation and program planning·2025

Same journal

Strategic Ability Updating in Concurrent Games by Coalitional Commitment.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2015

Same journal

Meta-Analysis of the First Facial Expression Recognition Challenge.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

Adjustable model-based fusion method for multispectral and panchromatic images.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

Face Feature Weighted Fusion Based on Fuzzy Membership Degree for Video Face Recognition.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

A New Adaptive Fast Cellular Automaton Neighborhood Detection and Rule Identification Algorithm.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

Same journal

Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012

See all related articles

Search research articles

Related Experiment Video

Updated: May 29, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Decentralized indirect methods for learning automata games.

Omkar Tilak¹, Ryan Martin, Snehasis Mukhopadhyay

¹Department of Computer and Information Science, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA. otilak@cs.iupui.edu

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|September 20, 2011

Summary

This summary is machine-generated.

This study introduces a novel decentralized pursuit learning algorithm for zero-sum and identical payoff games, offering computational advantages. The algorithm

Related Experiment Videos

Last Updated: May 29, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Area of Science:

Artificial Intelligence
Game Theory
Machine Learning

Background:

Learning automata games are crucial in AI and game theory.
Decentralized algorithms offer computational benefits over centralized ones.
Analyzing learning algorithms in nonstationary environments is challenging.

Purpose of the Study:

To propose a novel decentralized pursuit learning algorithm for zero-sum and identical payoff games.
To theoretically analyze the convergence of this decentralized algorithm in nonstationary environments.
To introduce a partial communication framework for learning automata games.

Main Methods:

Development of a decentralized version of the pursuit learning algorithm.
Theoretical analysis using a novel bootstrapping argument to prove convergence.
Simulation studies across various game scenarios.

Main Results:

The decentralized algorithm demonstrates significant computational advantages.
The bootstrapping argument successfully proves algorithm convergence in nonstationary environments.
Simulation results confirm fast and accurate convergence for the proposed algorithm.

Conclusions:

The novel decentralized pursuit learning algorithm is effective for zero-sum and identical payoff games.
This work provides the first theoretical analysis of such algorithms in these game types.
The partial communication framework unifies centralized and decentralized game models.