[freeciv-ai] Re: learning from experience

[Ross Wetmore <rwetmore@xxxxxxxxxxxx>]

Per I. Mathisen wrote:
[...]
> In any case, there is a problem: Changing context. A strategy that works
> fine in, say, gen 1, may not work as well in gen2. Some slight changes in
> server options might change context enough to throw its accumulated
> weights into question.
The problem with this is one of poor implementation. The AI needs a feedback
loop that can update weights or switch strategies (alternate way of phrasing
update weights) on a timeframe less than a game or release cycle.

> What you describe would be quite useful in order to optimize the AI. We
> could put researched weights into the rulesets. However, I am pessimistic
> about the state of AI research when it comes to being able to write an AI
> that can figure out on the fly and on its own new strategies and read
> something meaningful into accumulated statistical data. But I would be
> happy to be proven wrong.
>
>   - Per
Again, if the implementation is explicitly coded in fine detail, then you are
correct that this is going to be a total failure.

The solution is more successful if it is developed using a fuzzy feedback
flavour. Small tactical operations might be handled in a micro-managed
fashion, but overall strategy should not be explicitly planned. Rather it
should be handled as a weighted selection of responses to changing game
state where feedback parameters adjust the weighting selection on a chosen
timescale.

At any given moment, one makes the best selection on the instantaneous set
of strategic weights. But over a longer period, one adjusts or reselects the
strategic imperatives based on events/needs/success/failure feedback decisions.

Cheers,
RossW
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