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

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...
Lagrange Multipliers: Problem Solving01:30

Lagrange Multipliers: Problem Solving

A silo with a cylindrical base, flat bottom, and hemispherical roof is a common design in agricultural and industrial storage due to its structural efficiency and ease of construction. Optimizing its dimensions to maximize storage capacity for a given amount of material—i.e., a fixed surface area—is a classic problem in applied calculus and engineering design. The key parameters are the radius r of the base and the height h of the cylindrical section.The total volume of the silo is obtained by...
Agonism and Antagonism: Quantification01:14

Agonism and Antagonism: Quantification

When drugs are administered, they can elicit either an agonist or antagonist effect on the body. Agonism occurs when a drug activates a specific receptor, triggering a biological response. On the other hand, antagonism happens when a drug binds to the same receptors but blocks their activation, thereby preventing a biological response.
To quantify these effects, researchers use a dose-response curve, which provides valuable information about the potency and efficacy of a drug. Potency refers to...
Heterogeneous Catalysis01:22

Heterogeneous Catalysis

Heterogeneous catalysis involves a catalyst in a different phase from the reactants. It is a process where the catalyst and the reactants are in distinct phases, typically solid and gas or liquid.Most heterogeneous catalysts are metals, metal oxides, or acids. The list includes transition metals like iron (Fe), cobalt (Co), nickel (Ni), palladium (Pd), platinum (Pt), chromium (Cr), manganese (Mn), tungsten (W), silver (Ag), and copper (Cu). These metals possess partially vacant d orbitals that...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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...
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...

You might also read

Related Articles

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

Sort by
Same author

Stabilizing Topological States in ZrTe<sub>5</sub> from First-Principles Defect Physics.

Nano letters·2026
Same author

Povarov-type Reaction of Anilines, Aqueous Acetaldehyde, and <sup><i>t</i></sup>BuONO for Access to <i>N</i>-Nitroso-1,2,3,4-tetrahydroquinolines.

Organic letters·2026
Same author

Diagnostic association of ante-mortem biomarkers with cerebral amyloid angiopathy in a cohort with high Alzheimer's disease comorbidity.

Journal of Alzheimer's disease reports·2026
Same author

Gene regulatory landscape dissected by single-cell four-omics sequencing.

Nature·2026
Same author

Algorithm prediction of lifetime under high-power microwave based on T-type field plate HEMTs.

Nanotechnology·2026
Same author

scDIAGRAM: detecting chromatin compartments from individual single-cell Hi-C matrix without imputation or reference features.

Briefings in bioinformatics·2026
Same journal

A Survey on Human-Centric Voice-Face Multimodal Learning.

IEEE transactions on neural networks and learning systems·2026
Same journal

Vision-Assisted Foundation Model for Solving Multitask Vehicle Routing Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

Hierarchical Semantic Concept Modeling for Generalizable Myocardial Pathology Segmentation on Multisequence CMR Images.

IEEE transactions on neural networks and learning systems·2026
Same journal

Stability of Time-Varying Impulsive Systems With State-Dependent Delay and Its Application in Complex Networks.

IEEE transactions on neural networks and learning systems·2026
Same journal

Adaptive Learning Control of Uncertain Systems via Weight and Intrinsic Plasticity-Based Neural Networks.

IEEE transactions on neural networks and learning systems·2026
Same journal

TTP-SSFL: Test-Time Personalization Self-Supervised Federated Learning for Accelerating MR Image Reconstruction.

IEEE transactions on neural networks and learning systems·2026
See all related articles
  1. Home
  3. Fp3o: Enabling Proximal Policy Optimization In Multiagent Cooperation With Parameter-sharing Versatility.
  1. Home
  3. Fp3o: Enabling Proximal Policy Optimization In Multiagent Cooperation With Parameter-sharing Versatility.

Related Experiment Videos

FP3O: Enabling Proximal Policy Optimization in Multiagent Cooperation With Parameter-Sharing Versatility.

Lang Feng, Dong Xing, Junru Zhang

    IEEE Transactions on Neural Networks and Learning Systems
    |June 24, 2026

    View abstract on PubMed

    Summary
    This summary is machine-generated.

    This study introduces a versatile method for multiagent proximal policy optimization (PPO), enhancing generalizability across parameter-sharing configurations. The new full-pipeline PPO (FP3O) algorithm ensures consistent policy improvement for cooperative multiagent reinforcement learning.

    Related Experiment Videos

    Area of Science:

    • Artificial Intelligence
    • Machine Learning
    • Robotics

    Background:

    • Existing multiagent proximal policy optimization (PPO) methods struggle with generalizability across diverse parameter-sharing strategies (full, partial, nonparameter sharing).
    • Extending PPO's theoretical guarantees to cooperative multiagent reinforcement learning (MARL) remains a significant challenge.

    Purpose of the Study:

    • To introduce a general-purpose method for multiagent PPO that overcomes limitations in parameter-sharing versatility.
    • To develop a theoretically sound and practically effective algorithm for cooperative MARL.

    Main Methods:

    • Proposed the 'full-pipeline paradigm' utilizing equivalent advantage function decompositions.
    • Established multiple parallel optimization pipelines for enhanced flexibility.
  • Developed the practical algorithm 'full-pipeline PPO' (FP3O).

    • Main Results:

    • FP3O demonstrates consistent policy improvement across various parameter-sharing configurations.
    • Theoretical analysis confirms alignment between theory and practice for the proposed method.
    • Empirical evaluations show FP3O outperforms existing baselines on multiple MARL tasks.

    Conclusions:

    • FP3O offers a versatile and effective solution for multiagent PPO, addressing generalizability issues.
    • The method provides a theoretically and practically aligned guarantee for cooperative MARL.
    • FP3O exhibits remarkable versatility across all common parameter-sharing standards.