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instead of one). Given our incremental computation (detailed in the full version of the
paper), these quotes can be extracted from the order topic in constant time.
Anonymous Full Schedule Quote.
The third quote we consider provides to all agents
a full schedule of payments that would be required to exchange any feasible quantity
given the current state of the order topic. This can be viewed as a collection of marginal
unit quotes, one for each feasible quantity. The quote is anonymous because the same
values are provided to every agent. Note that only relevant payment-quantity pairs need
to be communicated to an agent: for a given payment, a quote for the minimum number
of units the agent needs to sell to get such payment, and the maximum number of units
the agent can buy with such payment. As for the marginal unit quote, the schedule may
not be monotone: the unit price to exchange various quantities may be increasing or
decreasing or mixed along the schedule.
Also like the marginal unit quote, the full schedule quote can be extracted directly
from the order topic given our incremental computation scheme, though of course ex-
tracting and communicating it will take time proportional to its size,
O
(
C
).
Non-Anonymous Full Schedule Quote.
The final quote we consider is similar to the
previous one, but each agent is provided with personalized values based on its existing
bid. More specifically, this quote provides agent
i
the schedule of payments calculated
by excluding from the order topic the bid sent by
i
.
Quote Discussion.
The four candidate quotes present distinct tradeoffs. The standard
and marginal-unit quotes are compact, but the more accurate one may be excessively
conservative when used as a guide for quantities greater than a single unit. The full
schedule quotes provide high-fidelity information, but may be too large to be reasonably
communicated in some applications.
We explore the implications of the various quote policies in our experiments be-
low. (Results for non-anonymous quotes are pending from ongoing experiments, not
reported here.) Of course, the worth of a quote is intimately tied to how the agents use
this information in their bidding. We discuss our assumptions about agent behavior in
Section 4.2 below.
2.4
Implementation
We implemented the AON auction as an extension of AB3D, a configurable auction
and market-game server developed at the University of Michigan [13]. AB3D provides
a flexible bid-processing architecture, with a rule-based scripting language to specify
particular auction policies and temporal control structure. The standard call market was
already supported by AB3D. To handle indivisible bidding, we added a new bid lan-
guage specifying quantity-payment schedules, and new matching, pricing, and quoting
modules implementing the algorithms and policies described above. In particular, we
implemented all four quoting candidates as selectable options. Parameters in the auction
script determine whether to allow AON bids, and if so, which of the available quoting
and pricing policies to employ.
