Scaling Instructable Agents Across Many Simulated Worlds
<|reference_start|>Scaling Instructable Agents Across Many Simulated Worlds: Building embodied AI systems that can follow arbitrary language instructions in any 3D environment is a key challenge for creating general AI. Accomplishing this goal requires learning to ground language in perception and embodied actions, in order to accomplish complex tasks. The Scalable, Instructable, Multiworld Agent (SIMA) project tackles this by training agents to follow free-form instructions across a diverse range of virtual 3D environments, including curated research environments as well as open-ended, commercial video games. Our goal is to develop an instructable agent that can accomplish anything a human can do in any simulated 3D environment. Our approach focuses on language-driven generality while imposing minimal assumptions. Our agents interact with environments in real-time using a generic, human-like interface: the inputs are image observations and language instructions and the outputs are keyboard-and-mouse actions. This general approach is challenging, but it allows agents to ground language across many visually complex and semantically rich environments while also allowing us to readily run agents in new environments. In this paper we describe our motivation and goal, the initial progress we have made, and promising preliminary results on several diverse research environments and a variety of commercial video games.<|reference_end|>
@article{sima team2024scaling,
    title={Scaling Instructable Agents Across Many Simulated Worlds},
    author={SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic
  Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max
  Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister,
  Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di
  Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie
  Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzales, Kshitij Gupta, Karol
  Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst,
  Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi
  Jasarevic, Laura Kampis, Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg,
  Kavya Kopparapu, Rory Lawton, Andrew Lampinen, Shane Legg, Alexander
  Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino,
  Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria
  Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valeria
  Oliveira, Yanko Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex
  Platonov, Ollie Purkiss, David Reichert, John Reid, Pierre Harvey Richemond,
  Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P.
  Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko
  Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi,
  Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong
  Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young},
    journal={arXiv preprint arXiv:2404.10179},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.10179},
    primaryClass={cs.RO cs.AI cs.HC cs.LG}
}