Author

R. Paleja

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Preprint Aug 2026

Composing Learned Robot Behaviors with Temporal Logic at Runtime

Executing Linear Temporal Logic (LTL) instructions with learned robot policies faces two practical challenges: demonstrations may cover individual behaviors without containing the temporal compositions requested at deployment, and semantic success predicates often provide little useful motor guidance through quantitati...

Moritz Zoellner, Anastasios Manganaris, A. H. Qureshi et al. · 1 citation

#artificial intelligence Preprint Sep 2026

Mitigating Retaliatory Algorithmic Collusion in Repeated Games

Reinforcement learning agents trained to maximize their own reward in repeated interactions can converge to supra-competitive outcomes resembling explicit collusion, without communication or shared design. Existing mitigation approaches are largely tied to specific economic settings, like two-sided platforms and auctio...

K. Sivachandran, R. Paleja · 1 citation

#machine learning Preprint Aug 2026

hint$^2$: Hierarchical World Models for Inference-Time Temporal Logic Guidance

This paper introduces hint, a method for guiding short-horizon policies toward satisfying complex LTL specifications at inference time using hierarchical world models, and shows that hint$^2$ can handle complex instructions on a real UR5e manipulator.

Moritz Zoellner, Anastasios Manganaris, A. H. Qureshi et al. · 1 citation