Jayden
@jaydenteoh.bsky.social
Undergraduate researcher. Interested in generalization, multi-objective reinforcement learning, and open-endedness | Looking for PhD in RL in 2026
My works: https://scholar.google.com/citations?user=GnHpLE8AAAAJ&hl=en
My works: https://scholar.google.com/citations?user=GnHpLE8AAAAJ&hl=en
Pinned
Jayden
@jaydenteoh.bsky.social
· Mar 5
On Generalization Across Environments In Multi-Objective Reinforcement Learning
Real-world sequential decision-making tasks often require balancing trade-offs between multiple conflicting objectives, making Multi-Objective Reinforcement Learning (MORL) an increasingly prominent f...
arxiv.org
Our work "On Generalization Across Environments in Multi-Objective Reinforcement Learning" has been accepted at ICLR 2025!
Paper: arxiv.org/abs/2503.00799
Code: github.com/JaydenTeoh/M...
Authors: Jayden Teoh, Pradeep Varakantham, Peter Vamplew (@amp1874.bsky.social)
More below --->
Paper: arxiv.org/abs/2503.00799
Code: github.com/JaydenTeoh/M...
Authors: Jayden Teoh, Pradeep Varakantham, Peter Vamplew (@amp1874.bsky.social)
More below --->
Been feeling FOMO from all the ICLR posts the past 2 days. Will finally be at the conference tomorrow. Please do come by our poster and I’m happy to chat! 😊
⏰: Sat, 26 Apr 3pm
📍: Hall 3 + Hall 2B Poster 374
⏰: Sat, 26 Apr 3pm
📍: Hall 3 + Hall 2B Poster 374
April 25, 2025 at 5:40 PM
Been feeling FOMO from all the ICLR posts the past 2 days. Will finally be at the conference tomorrow. Please do come by our poster and I’m happy to chat! 😊
⏰: Sat, 26 Apr 3pm
📍: Hall 3 + Hall 2B Poster 374
⏰: Sat, 26 Apr 3pm
📍: Hall 3 + Hall 2B Poster 374
Our work "On Generalization Across Environments in Multi-Objective Reinforcement Learning" has been accepted at ICLR 2025!
Paper: arxiv.org/abs/2503.00799
Code: github.com/JaydenTeoh/M...
Authors: Jayden Teoh, Pradeep Varakantham, Peter Vamplew (@amp1874.bsky.social)
More below --->
Paper: arxiv.org/abs/2503.00799
Code: github.com/JaydenTeoh/M...
Authors: Jayden Teoh, Pradeep Varakantham, Peter Vamplew (@amp1874.bsky.social)
More below --->
On Generalization Across Environments In Multi-Objective Reinforcement Learning
Real-world sequential decision-making tasks often require balancing trade-offs between multiple conflicting objectives, making Multi-Objective Reinforcement Learning (MORL) an increasingly prominent f...
arxiv.org
March 5, 2025 at 6:59 AM
Our work "On Generalization Across Environments in Multi-Objective Reinforcement Learning" has been accepted at ICLR 2025!
Paper: arxiv.org/abs/2503.00799
Code: github.com/JaydenTeoh/M...
Authors: Jayden Teoh, Pradeep Varakantham, Peter Vamplew (@amp1874.bsky.social)
More below --->
Paper: arxiv.org/abs/2503.00799
Code: github.com/JaydenTeoh/M...
Authors: Jayden Teoh, Pradeep Varakantham, Peter Vamplew (@amp1874.bsky.social)
More below --->
Reposted by Jayden
Our ICRL paper on generalization in multi-objective reinforcement learning is now on arxiv: arxiv.org/abs/2503.00799
This work lead by Jayden Teoh is the first to examine generalization of RL across multiple multi-objective environments, and is a great basis for an exciting new field of research.
This work lead by Jayden Teoh is the first to examine generalization of RL across multiple multi-objective environments, and is a great basis for an exciting new field of research.
On Generalization Across Environments In Multi-Objective Reinforcement Learning
Real-world sequential decision-making tasks often require balancing trade-offs between multiple conflicting objectives, making Multi-Objective Reinforcement Learning (MORL) an increasingly prominent f...
arxiv.org
March 4, 2025 at 8:42 PM
Our ICRL paper on generalization in multi-objective reinforcement learning is now on arxiv: arxiv.org/abs/2503.00799
This work lead by Jayden Teoh is the first to examine generalization of RL across multiple multi-objective environments, and is a great basis for an exciting new field of research.
This work lead by Jayden Teoh is the first to examine generalization of RL across multiple multi-objective environments, and is a great basis for an exciting new field of research.