
Deal or no deal? Training AI bots to negotiate - runesoerensen
https://code.facebook.com/posts/1686672014972296/deal-or-no-deal-training-ai-bots-to-negotiate
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paskster
Interesting that the chatbots learned to show "fake" interest in an item, just
to conceide it later in the negotiation process.

But I think what is missing, is the time component when negotiating with
humans. A negotiation process is usually better for humans if the negotiation
is quick and not dragging on too long.

And more importantly the chatbots never seemed to "walk away" from a deal. But
in real life, you sometimes have to walk away to show the other party, that
you are not a pushover. It would be interesting to enhance the model so that
chatbots negotiate repeatedly with each other and "remember" how the other
party behaves and how far you can push the other party to concede. Because
some negotiations really are zero sum games.

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al_chemist
> But in real life, you sometimes have to walk away to show the other party,
> that you are not a pushover.

AI consider this human behavior a bug.

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Spooky23
No, it's signaling that you're wasting time and need to move on.

Many situations cannot be resolved until you convince the other party that
their business model or position or assumptions are wrong. Walking away is the
only way to do that because it triggers escalation.

I had s sitstuiin recently where the account team couldn't get a term that we
needed. We basically told them to go away and stopped 2-3 other negotiations.
That let our counterparty get the resource he needed (SVP of product X) and
balance returned to the force.

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wlamond
It'd be interesting if the agents developed their own language during the
reinforcement learning stage that is unintelligible to humans but allows them
to quickly navigate the negotiation. They use the model trained in a
supervised way during the reinforcement learning stage to avoid this, but I'm
curious to see what the agent learns when paired against another reinforcement
learning agent.

Edit: Indeed, the paper says that not using the fixed agent trained on human
negotiation leads to unintelligible language from the agents.

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EGreg
Can we measure if the language is more efficient at getting deals done?

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wlamond
I bet we could. The length of each utterance, the number of exchanges between
agents, and the entropy of the symbols used in the utterances could give you
some measure of efficiency.

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phreeza
The most interesting thing to me is not the negotiation tactics that the
agents learn but the idea of coming up with a more easily quantifiable (and
therefore differentiable) quality metric for dialogue tasks.

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EGreg
And so it begins.

I am worried when computers start getting better than people at these kinds of
things. They already mastered heads-up poker.

Almost all of our systems rely on an inefficiency of an attacker - so they are
vulnerable.

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visarga
So in a very limited sense these agents have a theory of mind - they can infer
the beliefs and goals of their opponents and act accordingly. Agents/objects
can be in an exponential number of possible relative positions, but this
system factorizes structure from function.

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pmontra
It would be interesting to see what happens when new untrained bots start
negotiating with trained one. One new language for each pair of bots or one
common language that every new bot has to learn?

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Zpalmtree
>To prevent the algorithm from developing its own language, it was
simultaneously trained to produce humanlike language.

Not sure what this would look like, but I'd be interested to find out.

