We describe Concurrent ALisp, a language that allows the augmentation of reinforcement learning algorithms with prior knowledge about the structure of policies, and show by example how it can be used to write agents that learn to play a subdo-main of the computer game Stratagus.
Writing Stratagus-playing Agents in Concurrent ALisp
Writing Stratagus-playing Agents in Concurrent ALisp
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04:27 jim4 why haven't you added wc1 support? this project sucks. i'm only going to use freecraft
05:06 jim4 finished wc1 support yet? i've been waiting for 6 years
05:10 jim4 new things scare me
05:06 jim4 finished wc1 support yet? i've been waiting for 6 years
05:10 jim4 new things scare me
Re: Writing Stratagus-playing Agents in Concurrent ALisp
According to http://citeseerx.ist.psu.edu/viewdoc/su ... 1.1.108.75, this article was written in 2005.8 Conclusion
We have outlined an approach to writing programs that play
games like Stratagus using partial programming with concurrent
ALisp, and demonstrated its effectiveness on a subdomain
that would be difficult for conventional reinforcement
learning methods. In the near future, we plan to implement
our improved learning algorithm, and scale up to increasingly
larger subgames within Stratagus.
Who wants to bet they never followed through with their future plans?
Re: Writing Stratagus-playing Agents in Concurrent ALisp
They probably did in one of the other papers.
04:27 jim4 why haven't you added wc1 support? this project sucks. i'm only going to use freecraft
05:06 jim4 finished wc1 support yet? i've been waiting for 6 years
05:10 jim4 new things scare me
05:06 jim4 finished wc1 support yet? i've been waiting for 6 years
05:10 jim4 new things scare me