Pricing Strategies

We consider three pricing strategies, each of which makes very different demands on the required level of informational and computational power of agents:

GT

The game-theoretic strategy is designed to reproduce the mixed strategy game-theoretic equilibrium computed in the previous section, provided that it is employed by all seller agents. It makes use of full information about the buyer population, and assumes that its competitors also use the GT strategy. It therefore generates a price chosen randomly from the probability density function derived in the previous section.

MY

The myopically optimal, or myoptimal, pricing strategy [Kephart et al. 1998] uses information about all the buyer characteristics that factor into the buyer demand function, as well as the competitors' prices, but makes no attempt to account for competitors' pricing strategies. Instead, it is based on the assumption of static expectations: even if one seller is contemplating a price change under myoptimal pricing, this seller does not assume that this will elicit a response from its competitors; instead it assumes that competitors' prices will remain fixed.

The myoptimal seller uses all of the available information and the assumption of static expectations to perform an exhaustive search for the price that maximizes its expected profit . In our simulations, we compute according to Eqs. 7 and 8. The optimal price is guaranteed to be either the valuation v or below some competitor's price, where is the price quantum, or the smallest amount by which one seller may undercut another, set to 0.002 in these simulations. This limits the search for to S possible values.

DF

The derivative-following strategy is far less informationally intensive than either the myoptimal pricing strategy or the game-theoretic strategy. In particular, this strategy can be used in the absence of any knowledge or assumptions about one's competitors or the buyer demand function. A derivative follower simply experiments with incremental increases (or decreases) in its price, continuing to move its price in the same direction until the observed profitability level falls, at which point the direction of movement is reversed. The price increment is chosen randomly from a specified probability distribution; in the simulations described here the distribution was uniform between 0.01 and 0.02.