In StarCraft II, adding LLMs (to do/aid game-time thinking) will not help the agent in any way, I believe. That happens because inference has a quite large latency, especially as most of prompt changes with all the units moving, so tactical moves are out; strategic questions “what is the other player building” and “how many units do they already have” are better answered by card-counting counting visible units and inferring what’s the proportion of remaining resources (or scouting if possible).
I guess it is possible that bots’ algorithms are improved with LLMs but that requires a high-quality insight; not convinced that o1 or o3 give such insights.
That article is suspiciously scarce on what microcontrols units… well, glory to LLMs for decent macro management then! (Though I believe that capability is still easier to get without text neural networks.)
In StarCraft II, adding LLMs (to do/aid game-time thinking) will not help the agent in any way, I believe. That happens because inference has a quite large latency, especially as most of prompt changes with all the units moving, so tactical moves are out; strategic questions “what is the other player building” and “how many units do they already have” are better answered by
card-countingcounting visible units and inferring what’s the proportion of remaining resources (or scouting if possible).I guess it is possible that bots’ algorithms are improved with LLMs but that requires a high-quality insight; not convinced that o1 or o3 give such insights.
Ma et al 2023 is relevant here.
That article is suspiciously scarce on what microcontrols units… well, glory to LLMs for decent macro management then! (Though I believe that capability is still easier to get without text neural networks.)