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Correlated-Q (CE-Q) learning is introduced, a multiagent Q-learning algorithm based on the correlated equilibrium (CE) solution concept that generalizes both Nash-Q and Friend-and-Foe-Q.
Dynamic pricing by software agents
Shopbots and Pricebots
A simple economic model is proposed and analyzed, which is intended to quantify some of the likely impacts of a proliferation of shopbots and other economically-motivated software agents.
Strategic pricebot dynamics
A comparative study of four candidate price-setting strategies that meet informational and computational requirements: gametheoretic pricing (GT), myoptimalpricing (MY), derivative following (DF), and Q-learning (Q), which exhibits superior performance to all the others.
No-regret learning in convex games
This paper analyzes a spectrum of regret types which lie between external and swap regret, along with their corresponding equilibria, which lies between coarse correlated and correlated equilibrium.
Cyclic Equilibria in Markov Games
It is proved by construction that existing variants of value iteration cannot find stationary equilibrium policies in arbitrary general-sum Markov games, and it is proved empirically that value iteration finds cyclic equilibria in nearly all examples drawn from a random distribution of Markovgames.
The 2001 trading agent competition
The 2001 Trading Agent Competition was the second in a series of events aiming to shed light on research issues in automating trading strategies, suggesting that trading in online markets is a viable domain for highly autonomous agents.
Bidding under Uncertainty: Theory and Experiments
This paper describes a study of agent bidding strategies, assuming combinatorial valuations for complementary and substitutable goods, in three auction environments: sequential auctions, simultaneous…
Dynamic pricing strategies under a finite time horizon
The goals of the research are to explore the use of simulation as a tool to aid in the development of dynamic pricing strategies and to explicitly identify the market conditions under which the authors' example strategies, Goal-Directed and Derivative-Following, are successful.
Learning Curve: A Simulation-Based Approach to Dynamic Pricing
The following article presents the Learning Curve Simulator, a market simulator designed for analyzing agent pricing strategies in markets under finite time horizons and fluctuation buyer demand, and demonstrates the strength of a simulation-based approach to understandingAgent pricing strategies.