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

Inductive Reasoning00:59

Inductive Reasoning

60.7K
Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
60.7K
Principle of Virtual Work: Problem Solving01:13

Principle of Virtual Work: Problem Solving

1.2K
The principle of virtual work is an essential concept in the field of mechanics and engineering. This is used to solve problems related to the equilibrium of a structure or system. It is based on the assumption that if a system is in equilibrium, the work done by all the forces during a virtual displacement is zero. This principle is applied by considering virtual displacements of the system and the corresponding work done by internal and external forces.
To apply the principle of virtual work,...
1.2K
Self-Schemas02:16

Self-Schemas

31.2K
In general, a schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
31.2K
Deductive Reasoning01:16

Deductive Reasoning

55.9K
Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
55.9K
Cognitive Learning01:21

Cognitive Learning

459
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
459
Metacognition01:26

Metacognition

240
Metacognition is a conscious process where individuals are aware of their cognitive and executive processes, such as planning before solving a problem or self-monitoring during reading. For instance, a writer may need help with composing a piece. The situation involves a writer who is working on a piece of writing, but while doing so, they realize that something is missing. They notice that their characters lack depth or details. This realization occurs because the writer is reflecting on their...
240

You might also read

Related Articles

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

Sort by
Same author

Magnetic Resonance Spectroscopy Deep Learning with Magnetic Resonance Background Generator Enables In Vivo Metabolite Quantification of Hepatic Encephalopathy.

IEEE transactions on bio-medical engineering·2026
Same author

Cable bacteria drive electrochemical coupling and elemental cycling in rhizosphere: A review.

Ying yong sheng tai xue bao = The journal of applied ecology·2026
Same author

Functionalized carbon nanotube-assisted dual-mode CRISPR/Cas12a detection of hepatitis C virus via catalytic assembly circuit-driven Y-shaped dsDNA activators.

Biosensors & bioelectronics·2026
Same author

Atomically confined insertion for 2D strain and polarization engineered GaN electronics.

Nature communications·2026
Same author

Efficacy of tranexamic acid for prevention of heterotopic ossification after orthopedic surgery: a systematic review and meta-analysis.

BMC surgery·2026
Same author

Donor-Acceptor-Donor Type Diimidazole-Based Metal-Organic Framework for Photocatalytic C-O and C-C Bond Formation.

Inorganic chemistry·2026
Same journal

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Learning Shape Anchors for Holistic Indoor Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

Related Experiment Video

Updated: Jul 30, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

366

Knowledge-Based Embodied Question Answering.

Sinan Tan, Mengmeng Ge, Di Guo

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |May 17, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new Knowledge-based Embodied Question Answering (K-EQA) task. The proposed framework uses neural program synthesis and 3D scene graphs to enable agents to answer complex questions by integrating external knowledge and environmental exploration.

    More Related Videos

    Virtual Hand with Ambiguous Movement between the Self and Other Origin: Sense of Ownership and 'Other-Produced' Agency
    08:01

    Virtual Hand with Ambiguous Movement between the Self and Other Origin: Sense of Ownership and 'Other-Produced' Agency

    Published on: October 28, 2020

    5.7K
    Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
    06:53

    Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

    Published on: March 1, 2017

    13.3K

    Related Experiment Videos

    Last Updated: Jul 30, 2025

    Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
    05:47

    Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

    Published on: June 13, 2025

    366
    Virtual Hand with Ambiguous Movement between the Self and Other Origin: Sense of Ownership and 'Other-Produced' Agency
    08:01

    Virtual Hand with Ambiguous Movement between the Self and Other Origin: Sense of Ownership and 'Other-Produced' Agency

    Published on: October 28, 2020

    5.7K
    Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
    06:53

    Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

    Published on: March 1, 2017

    13.3K

    Area of Science:

    • Artificial Intelligence
    • Robotics
    • Computer Vision

    Background:

    • Existing Embodied Question Answering (EQA) struggles with questions requiring external knowledge.
    • Agents typically require explicit object identification in queries.
    • Complex, real-world scenarios necessitate knowledge integration for effective QA.

    Purpose of the Study:

    • To introduce a novel Knowledge-based Embodied Question Answering (K-EQA) task.
    • To develop a framework enabling agents to answer questions using external knowledge and environmental exploration.
    • To enhance agent capabilities for understanding and responding to complex, knowledge-dependent queries.

    Main Methods:

    • Proposed a novel framework based on neural program synthesis reasoning.
    • Integrated external knowledge with 3D scene graphs for joint reasoning.
    • Utilized 3D scene graphs as memory for visited environments to improve efficiency.
    • Enabled agent navigation and question answering within simulated environments.

    Main Results:

    • Demonstrated the framework's ability to answer complex, realistic questions in embodied environments.
    • Showcased improved efficiency in multi-turn question answering through scene graph memory.
    • Validated the approach's effectiveness in handling knowledge-intensive queries.
    • Confirmed applicability to multi-agent scenarios.

    Conclusions:

    • The proposed K-EQA framework successfully addresses limitations of traditional EQA by incorporating external knowledge.
    • Neural program synthesis combined with 3D scene graphs offers a powerful approach for intelligent agent navigation and question answering.
    • The method shows promise for more sophisticated human-robot interaction and complex task execution.