3 ms·
>senses, perception, pain, pleasure, fear, volition... a body! Yes! Almost all neural networks have no self-model and thus no self-awareness because they canno
by 7373737373 7y ago
>senses, perception, pain, pleasure, fear, volition... a body!
Yes! Almost all neural networks have no self-model and thus no self-awareness because they cannot perceive themselves. They only see the inputs. They do not see the result of their actions.
This makes developing a self-model impossible. They cannot develop an internal model of internal vs external causes. What their "boundary of influence" is. Differentiation between internal and external causes.
They are trained and then used, immutable, unlearning after training. Even if they could perceive their outputs during training and/or evaluation, they cannot perceive themselves otherwise, making it practically impossible to deduce by themselves what they even are. They can't inspect themselves.
The causal loop needs to be closed for all of this to happen.
- viuphiet 7y agoThe "self-model" you're talking about is the agent in the Reinforcement Learning framework. It moves between states in an environment and learns from reward it earns from each action.
- 7373737373 7y agoYes, although I wonder if, or how well these self-models develop in practice compared to the world-models. Say, if a 2D-agent has a rectangular body shape, it probably won't develop a high-level representation of that fact unless its actions allow it to perceive it accurately. Purely figuring that out from collisions produced by basic actions (rotate left, rotate right, move forward etc.) seems to be practically infeasible. It has neither sight (observing self-movements) nor self-touch (which would allow it to observe its boundaries and relate it to what it has seen).