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You don't need perfect simulation, just a good enough one. Simulation is like a dynamic, extensible dataset. Neural nets can learn from simulation not only in game play, but also in genetics, robotics and general reasoning. I think simulation is at the core of what will lead to AGI.

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My comment was is about inevitable philosophical gap between reality and any model or a simulation, which cannot be bridged in principle.

Yes, simulators as sources of sensory input to get similar experience are used, for example, to train airline pilots. Nevertheless, there is no airline which train its pilots on a simulator only. Algorithm, like a pilot, would learn a simulation, not reality.

That's true. I was thinking about using simulation as an addition to being embedded in the real world. Simulation is necessary to plan complex actions based on reinforcement learning (model based RL). When AI can do simulations, it can check a few steps ahead to see how things will go and select and act in a proactive way as to maximize rewards. When interacting with people, the AI will need to model people's state of mind and knowledge, in order to infer how they would act and react. When using a device, an AI would need to control it and know what to expect from it. In almost any non-trivial interaction, AI needs to simulate in order to adapt to situations. Since it is impossible to rewind reality (like a game) in order to try another action, the agent needs to do that in its imagination (simulator).

By the way, humans are good for simulating some things, but quite bad for others, and it still doesn't stop us from being the most intelligent agents. I think AI only needs to simulate a little ahead in order to act much more intelligently than today, because today, AI is mostly reactive, or feed-forward, like a simple reflex.

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