Recently, I always hear about the terms sim2sim, sim2real and real2real. Will anyone explain the meaning/motivation of these terms (in DL/RL research community)?
What are the challenges in this research area?
Anything intuitive would be appreciated!
Recently, I always hear about the terms sim2sim, sim2real and real2real. Will anyone explain the meaning/motivation of these terms (in DL/RL research community)?
What are the challenges in this research area?
Anything intuitive would be appreciated!
The abbreviations sim2sim, sim2real and real2real refer to techniques that can be used to transfer knowledge from one environment (e.g. in simulation) to another one (e.g. in the real world).
In sim2sim, knowledge acquired during one simulation is transferred to an agent (or robot) in another simulation. Similarly, in sim2real, knowledge acquired during the simulation is used in a real-world problem (or environment). Finally, in real2real, knowledge acquired in a real-world problem can be transferred to another agent in another real-world problem.
The main challenges are related to the differences that exist between one environment and the other (either in simulation or in the real-world). For example, in sim2real, the simulation is almost never a perfect model of the real-world environment, so an agent trained in a simulation will probably not behave optimally in the real-world environment, which is often a lot more complex than the simulated environment. However, it is often the case that a robot needs to be trained in simulation, given that a robot trained in a real-world environment is subject to crashes.