Hybrid Conferencee

International Conference on Reinforcement Learning and Machine Learning (ICRLML - 26)

16th - 17th September 2026 | Maseru, Lesotho

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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Maseru. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Maseru event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Maseru conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Maseru, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Maseru."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICRLML aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Machine Learning, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Applications of reinforcement learning in robotics
02
Deep reinforcement learning techniques
03
Multi-agent reinforcement learning systems
04
Reinforcement learning for game AI
05
Challenges in reinforcement learning applications
06
Reinforcement learning in autonomous vehicles
07
Policy gradient methods in RL
08
Reinforcement learning for resource management
09
Exploration vs exploitation in RL
10
Transfer learning in reinforcement learning
11
Reinforcement learning for recommendation systems
12
Real-world applications of RL algorithms
13
Reinforcement learning in healthcare optimization
14
Ethics of reinforcement learning applications
15
Reinforcement learning for financial trading
16
Hierarchical reinforcement learning approaches
17
Reinforcement learning in natural language processing
18
Robustness of RL algorithms in practice
19
Reinforcement learning for energy management
20
Future trends in reinforcement learning research