Fetching the paper…
Reading the bibliography…
To facilitate the development of new models to bridge the gap between machine and human social intelligence, the recently proposed Baby Intuitions Benchmark (arXiv:2102.11938) provides a suite of tasks designed to evaluate commonsense reasoning about agents' goals and actions that even young infants exhibit.
Taking the intentional stance at 12 months of age
György Gergely, Zoltán Nádasdy, Gergely Csibra, and Szilvia Bíró · 1995
Earlier work this paper cites.
Learning to act using real-time dynamic programming
Andrew G Barto, Steven J Bradtke, and Satinder P Singh · 1995
Earlier work this paper cites.
Teleological reasoning in infancy: The infant’s naive theory of rational action: A reply to Premack and Premack
György Gergely and Gergely Csibra · 1997
Earlier work this paper cites.
Early reasoning about desires: evidence from 14-and 18-month-olds
Betty M Repacholi and Alison Gopnik · 1997
Earlier work this paper cites.
PDDL - the Planning Domain Definition Language, 1998
Drew McDermott, Malik Ghallab, Adele Howe, Craig Knoblock, Ashwin Ram, Manuela Veloso, Daniel Weld, and David Wilkins · 1998
Earlier work this paper cites.
Infants’ ability to distinguish between purposeful and non-purposeful behaviors
Amanda L Woodward · 1999
Earlier work this paper cites.
The structure and function of explanations
Tania Lombrozo · 2006
Earlier work this paper cites.
Infants track action goals within and across agents
Jennifer Sootsman Buresh and Amanda L Woodward · 2007
Earlier work this paper cites.
Action understanding as inverse planning
Chris L Baker, Rebecca Saxe, and Joshua B Tenenbaum · 2009
Cited alongside, same era.
Hierarchical Bayesian inverse reinforcement learning
Jaedeug Choi and Kee-Eung Kim · 2014
Cited alongside, same era.
Infants learn enduring functions of novel tools from action demonstrations
Mikołaj Hernik and Gergely Csibra · 2015
Cited alongside, same era.
Shifting goals: Effects of active and observational experience on infants’ understanding of higher order goals
Sarah A Gerson, Neha Mahajan, Jessica A Sommerville, Lauren Matz, and Amanda L Woodward · 2015
Cited alongside, same era.
Six-month-old infants expect agents to minimize the cost of their actions
Shari Liu and Elizabeth S Spelke · 2017
Cited alongside, same era.
Probabilistic programs for inferring the goals of autonomous agents
The naive utility calculus as a unified, quantitative framework for action understanding
Julian Jara-Ettinger, Laura Schulz, and Josh Tenenbaum · 2019
Later among the works it cites.
Gen: a general-purpose probabilistic programming system with programmable inference
Marco F Cusumano-Towner, Feras A Saad, Alexander K Lew, and Vikash K Mansinghka · 2019
Later among the works it cites.
Online Bayesian goal inference for boundedly rational planning agents
Tan Zhi-Xuan, Jordyn Mann, Tom Silver, Josh Tenenbaum, and Vikash Mansinghka · 2020
Later among the works it cites.
AGENT: A benchmark for core psychological reasoning
Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin Smith, Shari Liu, Dan Gutfreund, Elizabeth Spelke, Joshua Tenenbaum, and Tomer Ullman · 2021
Later among the works it cites.
Baby Intuitions Benchmark (BIB): Discerning the goals, preferences, and actions of others
Kanishk Gandhi, Gala Stojnic, Brenden M Lake, and Moira R Dillon · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Marco F Cusumano-Towner, Alexey Radul, David Wingate, and Vikash K Mansinghka · 2017
Cited alongside, same era.
Neil C Rabinowitz, Frank Perbet, H Francis Song, Chiyuan Zhang, SM Eslami, and Matthew Botvinick · 2018
Cited alongside, same era.
Modeling the mistakes of boundedly rational agents within a Bayesian theory of mind
Arwa Alanqary, Gloria Z Lin, Joie Le, Tan Zhi-Xuan, Vikash K Mansinghka, and Joshua B Tenenbaum · 2021
Later among the works it cites.
3DP3: 3D scene perception via probabilistic programming
Nishad Gothoskar, Marco Cusumano-Towner, Ben Zinberg, Matin Ghavamizadeh, Falk Pollok, Austin Garrett, Josh Tenenbaum, Dan Gutfreund, and Vikash Mansinghka · 2021
Later among the works it cites.