no code implementations • 25 Apr 2024 • Andres Campero
This report enlists 13 functional conditions cashed out in computational terms that have been argued to be constituent of conscious valenced experience.
no code implementations • 24 Jun 2022 • Andres Campero, Michelle Vaccaro, Jaeyoon Song, Haoran Wen, Abdullah Almaatouq, Thomas W. Malone
In this case, we find a speed improvement ratio of 1. 27 (a 27% improvement).
no code implementations • 27 Jul 2021 • Pedro A. Tsividis, Joao Loula, Jake Burga, Nathan Foss, Andres Campero, Thomas Pouncy, Samuel J. Gershman, Joshua B. Tenenbaum
Here we propose a new approach to this challenge based on a particularly strong form of model-based RL which we call Theory-Based Reinforcement Learning, because it uses human-like intuitive theories -- rich, abstract, causal models of physical objects, intentional agents, and their interactions -- to explore and model an environment, and plan effectively to achieve task goals.
5 code implementations • ICLR 2021 • Andres Campero, Roberta Raileanu, Heinrich Küttler, Joshua B. Tenenbaum, Tim Rocktäschel, Edward Grefenstette
A key challenge for reinforcement learning (RL) consists of learning in environments with sparse extrinsic rewards.
no code implementations • 6 Sep 2018 • Andres Campero, Aldo Pareja, Tim Klinger, Josh Tenenbaum, Sebastian Riedel
Our approach is neuro-symbolic in the sense that the rule pred- icates and core facts are given dense vector representations.
no code implementations • 23 Oct 2017 • Andres Campero, Bjarke Felbo, Joshua B. Tenenbaum, Rebecca Saxe
Cognitive science has proposed appraisal theory as a view on human emotion with previous research showing how human-rated abstract event features can predict fine-grained emotions and capture the similarity space of neural patterns in mentalizing brain regions.