The International Research Conference Aims and Objectives
The International Research Conference is a federated organization dedicated to bringing together a significant number of diverse scholarly events for presentation
within the conference program. Events will run over a span of time during the conference depending on the number and length of the presentations.
With its high quality, it provides an exceptional value for students, academics and industry researchers.
International Conference on Artificial Intelligence and Human Learning
aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of
Artificial Intelligence and Human Learning.
It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations,
trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of Artificial Intelligence and Human Learning.
Call for Contributions
Prospective authors are kindly encouraged to contribute to and help shape the conference through submissions of their research abstracts, papers and e-posters.
Also, high quality research contributions describing original and unpublished results of conceptual, constructive, empirical, experimental, or
theoretical work in all areas of Artificial Intelligence and Human Learning are cordially invited for presentation at the conference.
The conference solicits contributions of abstracts, papers and e-posters that address themes and topics of the conference, including figures, tables and references of
novel research materials.
Guidelines for Authors
Please ensure your submission meets the conference's strict guidelines for accepting scholarly papers.
Downloadable versions of the check list for
Full-Text Papers and
Abstract Papers.
Please refer to the
Paper Submission Guideline,
Abstract Submission Guideline and
Author Information
before submitting your paper.
Conference Proceedings
All submitted conference papers will be blind peer reviewed by three competent reviewers.
The peer-reviewed conference proceedings are indexed in the Open Science Index,
Google Scholar,
Semantic Scholar,
Zenedo,
BASE,
WorldCAT,
Sherpa/RoMEO,
and other index databases. Impact Factor Indicators.
Special Journal Issues
19. International Conference on Artificial Intelligence and Human Learning has teamed up with the Special Journal Issue on
Artificial Intelligence and Human Learning.
A number of selected high-impact full text papers will also be considered for the special journal issues.
All submitted papers will have the opportunity to be considered for this Special Journal Issue.
The paper selection will be carried out during the peer review process as well as at the conference presentation stage.
Submitted papers must not be under consideration by any other journal or publication.
The final decision for paper selection will be made based on peer review reports by the Guest Editors and the Editor-in-Chief jointly.
Selected full-text papers will be published online free of charge.
Conference Sponsor and Exhibitor Opportunities
The Conference offers the opportunity to become a conference sponsor or exhibitor.
To participate as a sponsor or exhibitor, please download and complete the
Conference Sponsorship Request Form.
Selected Papers
-
Safe and Efficient Deep Reinforcement Learning Control Model: A Hydroponics Case Study
Almutasim Billa A. Alanazi, Hal S. Tharp
-
An Approach for the Prediction of Cardiovascular Diseases
Nebi Gedik
-
Prediction of Cardiovascular Disease by Applying Feature Extraction
Nebi Gedik
-
Detecting Fake News: A Natural Language Processing, Reinforcement Learning, and Blockchain Approach
Ashly Joseph, Jithu Paulose
-
Robot Exploration and Navigation in Unseen Environments Using Deep Reinforcement Learning
Romisaa Ali
-
Personalized Email Marketing Strategy: A Reinforcement Learning Approach
Lei Zhang, Tingting Xu, Jun He, Zhenyu Yan, Roger Brooks
-
Artificial Intelligence: A Comprehensive and Systematic Literature Review of Applications and Comparative Technologies
Z. M. Najmi
-
Distributed System Computing Resource Scheduling Algorithm Based on Deep Reinforcement Learning
Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar
-
Deep Reinforcement Learning for Optimal Decision-making in Supply Chains
Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol
-
A Control Model for Improving Safety and Efficiency of Navigation System Based on Reinforcement Learning
Almutasim Billa A. Alanazi, Hal S. Tharp
-
Robot Movement Using the Trust Region Policy Optimization
Romisaa Ali
-
Improved Computational Efficiency of Machine Learning Algorithms Based on Evaluation Metrics to Control the Spread of Coronavirus in the UK
Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick
-
Optimizing Data Evaluation Metrics for Fraud Detection Using Machine Learning
Jennifer Leach, Umashanger Thayasivam
-
Deep Reinforcement Learning Approach for Trading Automation in the Stock Market
Taylan Kabbani, Ekrem Duman
-
Rapid Study on Feature Extraction and Classification Models in Healthcare Applications
S. Sowmyayani
Digital Program consists of the e-proceedings book which is available online-only
and includes the conference communications (proceedings abstracts and papers).
Registered participants can access the digitally available conference
proceedings ( and certificates ) by visiting their profile pages.
Machine learning and cognitive science
Cognitive systems and learning methods
Human learning systems and artificial learning systems
Neural basis of human learning systems
Artificial neural networks
Unsupervised learning
Factor analysis
Multidimensional scaling
Mixture models (finite and infinite) for classification
Spectral clustering
Collaborative filtering” with low-rank factorizations
Nonlinear manifold learning with graph-based approximations
Supervised learning
Perceptrons
Multi-layer perceptrons
Kernel-based classification
Bayesian concept learning
Reinforcement learning
Temporal difference learning
| Abstracts/Full-Text Paper Submission Deadline |
|
November 28, 2024 |
| Notification of Acceptance/Rejection |
|
December 13, 2024 |
| Final Paper (Camera Ready) Submission & Early Bird Registration Deadline |
|
December 26, 2024 |
| Conference Dates |
|
January 30-31, 2025 |
