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Interesting blog-post. I found some similarities with what occurred with Deepmind's Alphastar AI. One of the weaknesses that seem to manifest in this piece to
by CyberRage 6y ago
Interesting blog-post.
I found some similarities with what occurred with Deepmind's Alphastar AI.
One of the weaknesses that seem to manifest in this piece too is the handling of unfamiliar scenarios.
The AI is very confused once it experiences something that was rarely seen in its learning data. Destroyer's big drones confused the bot quite a bit.
Deepmind solved it by intentionally creating agents that introduce different\bizzare strategies(which they called exploiters) in order to develop robustness against such strategies.
- cwinter 6y agoThe bot has actually never seen Destroyer's big drones during training even once, so I found it somewhat surprising that it even works as well as it does! Completely agree that adding something like the "League" used by AlphaStar would be one of the top priorities if you wanted to push this project further. I don't think CodeCraft is sufficiently complex to really allow for several very distinct strategies in the same way as StarCraft II, but I would still expect training against a larger pool of more diverse agents to increase robustness quite a bit.
- CyberRage 6y agoWhat amazes me at the end of the day is that brute-forcing seem to do much better than I initially thought it would do. Trying random stuff just sounds stupid but with enough compute and data, I guess it could overpower smart creatures like us. I agree that CodeCraft is vastly simpler than StarCraft but the idea is the same. just try random stuff(sometimes with better logic behind it) until something works and then optimize it to perfection.
- hntrader 6y agoThat randomness has to be massively constrained, though. Well over 99.9 percent of inputs are guaranteed to lead to bad results. For example if we're randomly way pointing a drone, we're almost guaranteed not to be sending it somewhere useful.