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cs.AI2026
CEDAR: Automata as Verifiable Interfaces for Language-Guided Embodied Action
Lekai Chen, Alvaro Velasquez, Ashutosh Trivedi
Natural-language tasking of embodied agents is rarely just goal specification: users also impose constraints that must persist while the world changes. Code-generating LLM agents c…
cs.AI2025
Average Reward Reinforcement Learning for Omega-Regular and Mean-Payoff Objectives
Milad Kazemi, Mateo Perez, Fabio Somenzi +3
Recent advances in reinforcement learning (RL) have renewed interest in reward design for shaping agent behavior, but manually crafting reward functions is tedious and error-prone.…