Robby Costales

My name is Robby Costales and I am a machine learning researcher focused on developing adaptive, open-ended agents that can explore and learn across complex, evolving task distributions. I am currently a Research Scientist Intern at Google DeepMind in Mountain View, and am also completing my PhD in computer science at the University of Southern California, advised by Prof. Stefanos Nikolaidis in the ICAROS lab.

Experience

Google DeepMind (Gemini)

💼 Research Scientist Intern (present)

University of Southern California (Viterbi School of Engineering)

🎓 Ph.D. Candidate in Computer Science (present)

Google Research (Brain Team)

💼 Student Researcher (2022)

Columbia University (Fu Foundation School of Engineering)

🎓 B.S. in Computer Science - Intelligent Systems (2020)

Bard College at Simon's Rock

🎓 A.A. (2017) and B.A. in Computer Science (2020)

Selected publications

Enabling Adaptive Agent Training in Open-Ended Simulators by Targeting Diversity [Site] [Paper] [Code]

R Costales, S Nikolaidis

Neural Information Processing Systems (NeurIPS) 2024

An evolutionary approach for generating diverse tasks to train adaptive agents in open-ended simulators.

ALMA: Hierarchical Learning for Composite Multi-Agent Tasks [Paper] [Code]

S Iqbal, R Costales, F Sha

Neural Information Processing Systems (NeurIPS) 2022

A general learning method for leveraging structured multi-agent tasks, resulting in sophisticated coordination behavior and outperforming competitive MARL baselines.

Possibility Before Utility: Learning And Using Hierarchical Affordances [Paper] [Code]

R Costales, S Iqbal, F Sha

🏅 (Spotlight) Int. Conf. on Learning Representations (ICLR) 2022

A hierarchical reinforcement learning (HRL) approach that learns a model of affordances to proune impossible subtasks for more effective learning.