Can LLMs make trade-offs involving stipulated pain and pleasure states?

This study investigates whether large language models (LLMs) can recreate the motivational force of pleasure and pain in decision-making scenarios, a question relevant to debates on LLM sentience. Results from a simple game reveal that some LLMs adjust their behavior based on the intensity of pain penalties and pleasure rewards, suggesting graded sensitivity, while others display fixed prioritization patterns, offering insights into their capacity for valenced decision-making.