Feb. 27, 2024, 5:44 a.m. | Jorge Ram\'irez-Ruiz, Dmytro Grytskyy, Chiara Mastrogiuseppe, Yamen Habib, Rub\'en Moreno-Bote

cs.LG updates on arXiv.org arxiv.org

arXiv:2205.10316v2 Announce Type: replace-cross
Abstract: Most theories of behavior posit that agents tend to maximize some form of reward or utility. However, animals very often move with curiosity and seem to be motivated in a reward-free manner. Here we abandon the idea of reward maximization, and propose that the goal of behavior is maximizing occupancy of future paths of actions and states. According to this maximum occupancy principle, rewards are the means to occupy path space, not the goal per …

abstract agents animals arxiv behavior cs.ai cs.lg curiosity form free intrinsic motivation path posit q-bio.nc space state type utility

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US