RCC seminar: Embodied agents as scientific assistants
Channel: UQ Research Computing Centre
Date: 2023-11-14

ABSTRACT:
I discuss the potentially transformative potential of embodied agents as next-generation scientific assistants. I begin by defining embodied agents — computational entities that interact with the world through physical bodies or representations, often leveraging sensorimotor experiences to learn and act. I then explore three primary facets of their integration:

 • Cognitive Collaboration: How embodied agents, with machine learning and data-processing capabilities, can complement the cognitive processes of human scientists, offering real-time data analysis, hypothesis generation, and even experimental design suggestions.

 • Physical Interaction: Embodied agents can engage physically with their environment, enabling applications ranging from precision tasks in bio-labs to advanced simulations on supercomputers.

 • Ethical and Philosophical Implications: Embodied agents raise questions regarding ethical use, the preservation of human intuition in science, and the possible redefinition of scientific discovery in an age where machines can potentially theorize and validate.

Concluding, I invite participants to envision a future where human scientists and embodied agents collaborate to enable accelerated scientific discoveries. 

BIOGRAPHY:
Ian Foster is the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago, and Distinguished Fellow and Director of the Data Science and Learning Division at Argonne National Laboratory.

He has a BSc degree from the University of Canterbury, New Zealand, and a PhD from Imperial College, United Kingdom, both in computer science.
His research is in distributed, parallel, and data-intensive computing technologies, and their applications to scientific problems.

He is a fellow of the AAAS, ACM, BCS, and IEEE, and has received the BCS Lovelace Medal; IEEE Babbage, Goode, and Kanai awards; and ACM/IEEE Ken Kennedy award.