no code implementations • 5 Aug 2023 • Chathura Gamage, Vimukthini Pinto, Matthew Stephenson, Jochen Renz
We believe that the tasks generated using our proposed methodology can facilitate a nuanced evaluation of physical reasoning agents, thus paving the way for the development of agents for more sophisticated real-world applications.
1 code implementation • 3 Mar 2023 • Chathura Gamage, Vimukthini Pinto, Cheng Xue, Peng Zhang, Ekaterina Nikonova, Matthew Stephenson, Jochen Renz
But is it enough to only have physical reasoning capabilities to operate in a real physical environment?
no code implementations • 28 Jul 2022 • Ekaterina Nikonova, Cheng Xue, Vimukthini Pinto, Chathura Gamage, Peng Zhang, Jochen Renz
In this paper, we propose to define the novelty reaction difficulty as a relative difficulty of performing the known task after the introduction of the novelty.
1 code implementation • 31 Aug 2021 • Cheng Xue, Vimukthini Pinto, Chathura Gamage, Ekaterina Nikonova, Peng Zhang, Jochen Renz
Inspired by how human IQ is calculated, we define the physical reasoning quotient (Phy-Q score) that reflects the physical reasoning intelligence of an agent using the physical scenarios we considered.
1 code implementation • 17 Jun 2021 • Cheng Xue, Vimukthini Pinto, Chathura Gamage, Peng Zhang, Jochen Renz
In this paper, we propose a new benchmark for physical reasoning that allows us to test individual physical reasoning capabilities.
no code implementations • 3 Jun 2021 • Chathura Gamage, Matthew Stephenson, Vimukthini Pinto, Jochen Renz
The Angry Birds AI competition has been held over many years to encourage the development of AI agents that can play Angry Birds game levels better than human players.
