5 papers · 1 filter
Next-Latent Prediction Transformers Learn Compact World Models
Jayden Teoh, Manan Tomar, Kwangjun Ahn +7
Transformers replace recurrence with a memory that grows with sequence length and self-attention that enables ad-hoc lookups over past tokens. Consequently, they lack an inherent i…
On Discovering Algorithms for Adversarial Imitation Learning
Shashank Reddy Chirra, Jayden Teoh, Praveen Paruchuri +1
Adversarial Imitation Learning (AIL) methods, while effective in settings with limited expert demonstrations, are often considered unstable. These approaches typically decompose in…
On Generalization Across Environments In Multi-Objective Reinforcement Learning
Jayden Teoh, Pradeep Varakantham, Peter Vamplew
Real-world sequential decision-making tasks often require balancing trade-offs between multiple conflicting objectives, making Multi-Objective Reinforcement Learning (MORL) an incr…
Improving Environment Novelty Quantification for Effective Unsupervised Environment Design
Jayden Teoh, Wenjun Li, Pradeep Varakantham
Unsupervised Environment Design (UED) formalizes the problem of autocurricula through interactive training between a teacher agent and a student agent. The teacher generates new tr…
The Elicitation Game: Evaluating Capability Elicitation Techniques
Felix Hofstätter, Teun van der Weij, Jayden Teoh +3
Capability evaluations are required to understand and regulate AI systems that may be deployed or further developed. Therefore, it is important that evaluations provide an accurate…