ΑΙhub.org
 

Sony’s Gran Turismo Sophy project wins the ACM SIGAI Industry Award


by
27 July 2022



share this:
ACM SIGAI logo

As part of a special industry session at IJCAI-ECAI 2022, the 2022 ACM SIGAI Industry Award for Excellence in Artificial Intelligence was presented to the team behind Sony’s Gran Turismo Sophy project. This project was developed by Sony AI, Sony Interactive Entertainment and Polyphony Digital.

The award committee explain what the Gran Turismo Sophy project involved, and the significance and impact of this work:

Gran Turismo (GT) Sophy is a collection of agents trained using reinforcement learning (RL) techniques to race in Gran Turismo, a hyper-realistic, physics-based automotive racing simulator. The GT Sophy team developed novel, state-of-the-art RL methods for this purpose. Racing against some of the world’s best e-sports drivers, GT Sophy has not only performed at world-class levels, it also won a team event in October 2021 by an impressive margin. GT Sophy has demonstrated that state-of-the-art RL can be applied effectively to continuous control problems requiring performance at the edge of human capabilities, while respecting the informal norms and protocols associated with racing. Apart from the impact on gaming, the technology offers potential societal benefits in areas such as simulation-based training and autonomous vehicle development, among others.

GT racing car on trackImage credit: Sony AI America.

Peter Wurman, Director of Sony AI America, gave a keynote talk at IJCAI-ECAI about the project. He spoke about how the Sony AI team trained their agents, combining model-free deep reinforcement learning algorithms with mixed scenario training. This way they were able to learn an integrated control policy that combined speed with tactics. He showed the evolution of the agents and how they improved various facets of performance, such as overtaking.

One of the aspects that the team considered was racing etiquette. They wanted their agents to adhere to racing’s rules, which in competitions, just like in real-life motor racing, are enforced somewhat subjectively by human stewards. The team didn’t want their agents to race too aggressively, as, ultimately, they want it to be enjoyable to play against. To this end, they constructed a reward function that enables to agents to be competitive whilst still racing within the spirit of good sportspersonship.

As part of the talk there were some video demonstrations of the agents competing against world-class human players, including some footage from a head-to-head competition against four of the world’s best Gran Turismo drivers, which GT Sophy beat.

You can find out more about this work on the team’s project page.

The project leads: Peter R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J. Walsh, Peter Stone, Michael Spranger

The full list of team members: Peter R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Piyush Khandelwal, Varun Kompella, HaoChih Lin, Patrick MacAlpine, Declan Oller, Takuma Seno, Craig Sherstan, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead, Peter Dürr, Peter Stone, Michael Spranger, Hiroaki Kitano

About the award

The ACM SIGAI Industry Award for Excellence in Artificial Intelligence (AI) is given annually to individuals or teams who have transferred original academic research into AI applications in recent years in ways that demonstrate the power of AI techniques via a combination of the following features: originality of the research novelty and technical excellence of the approach; importance of AI techniques to the approach; and actual or predicted societal impact of the application.



tags:


Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

Statistical or embodied? Comparing people and LLMs in their processing of color metaphors: an interview with Douglas Guilbeault

  09 Jun 2026
We learn what implications color metaphors and synaesthesia have for human and AI cognition.

The Good Robot podcast: the battle over data centres with Tara Merk

  08 Jun 2026
Eleanor Drage speaks with Tara Merk about how community-owned data centers could transform digital ownership and challenge the dominance of Big Tech.

Congratulations to the #AAMAS2026 best paper award winners

  05 Jun 2026
Find out who won in the categories of best paper, best student paper, and best blue sky paper.

Interview with AAAI Fellow Sanmay Das: multiagent systems

  04 Jun 2026
We find out more about multi-agent research for the allocation of scarce societal resources.

Design tweaks promote responsible AI use for environmental protection, research shows

  03 Jun 2026
Systems that ask users to pause to consider AI’s energy consumption and environmental impacts are likely to reduce unnecessary AI use

An AI solution to an 80‑year‑old problem has shocked mathematicians

  02 Jun 2026
An OpenAI model has been used to find a counterexample to a famous conjecture made by legendary Hungarian mathematician Paul Erdős.

Forthcoming machine learning and AI seminars: June 2026 edition

  01 Jun 2026
A list of free-to-attend AI-related seminars that are scheduled to take place between 1 June and 31 July 2026.

Image Empire – a new short film from Alan Warburton

  29 May 2026
An animated fairytale about the fusion of the real and the virtual within contemporary AI models.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence