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Imagine a swarm of small robots, say drones with sufficient compute power on board. If I understand the repercussions of this correctly, could this be applied
by leblancfg 9y ago
Imagine a swarm of small robots, say drones with sufficient compute power on board.
If I understand the repercussions of this correctly, could this be applied so that the swarm be able to learn from the mistakes of a single individual?
- gwern 9y agoYes, but only if they are dispersed and not in a swarm. Once the agents are interacting with each other in the swarm, the usual RL methods slow down because now the 'environment' looks like it's changing every timestep (because your fellow robots are executing slightly different policies than you and your policy has been learned on the assumption of older policies). But of course there are various RL algorithms for dealing with having multiple interacting agents, for example, for Starcraft environments (in SC, there's only one player/mouse/keyboard, true, but the idea there is that multiple-agent RL methods have the advantage of, instead of learning one giant master NN to do everything, you can let individual smaller NNs control a few or just one unit and then they can coordinate for attacks).