DP15880 Artificial intelligence and Pricing: The Impact of Algorithm Design
The behavior of artificial intelligences algorithms (AIAs) is shaped
by how they learn about their environment. We compare the prices
generated by AIAs that use different learning protocols when there
is market interaction. Asynchronous learning occurs when the AIA
only learns about the return from the action it took. Synchronous
learning occurs when the AIA conducts counterfactuals to learn about
the returns it would have earned had it taken an alternative action.
The two lead to markedly different market prices. When future profits
are not given positive weight by the AIA, synchronous updating leads
to competitive pricing, while asynchronous can lead to pricing close
to monopoly levels. We investigate how this result varies when either
counterfactuals can only be calculated imperfectly and/or when the
AIA places a weight on future profits.
