Machine Learning
Multi-Attribute Dynamic Pricing for Online Markets Using Intelligent Agents
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Bilateral Negotiation Decisions with Uncertain Dynamic Outside Options
WEC '04 Proceedings of the First IEEE International Workshop on Electronic Contracting
Detecting Regime Shifts: The Causes of Under- and Overreaction
Management Science
Modeling opponent decision in repeated one-shot negotiations
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
CMieux: adaptive strategies for competitive supply chain trading
ACM SIGecom Exchanges
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Introduction to Logistics Systems Planning and Control (Wiley Interscience Series in Systems and Optimization)
A predictive empirical model for pricing and resource allocation decisions
Proceedings of the ninth international conference on Electronic commerce
Adaptive strategies for predicting bidding prices in supply chain management
Proceedings of the 10th international conference on Electronic commerce
Optimal pricing for mobile manufacturers in competitive market using genetic algorithm
Expert Systems with Applications: An International Journal
Flexible decision control in an autonomous trading agent
Electronic Commerce Research and Applications
TacTex-05: a champion supply chain management agent
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Efficient statistical methods for evaluating trading agent performance
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Detecting and forecasting economic regimes in multi-agent automated exchanges
Decision Support Systems
Identifying and forecasting economic regimes in TAC SCM
AMEC'05 Proceedings of the 2005 international conference on Agent-Mediated Electronic Commerce: designing Trading Agents and Mechanisms
Learning approaches for developing successful seller strategies in dynamic supply chain management
Information Sciences: an International Journal
Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business
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In today's complex supply chains, product pricing is a vital, yet non-trivial task. We propose a product pricing approach using adaptive real-time probability of acceptance estimations based on economic regimes. Radial Basis Function Networks are trained to estimate parameters for double-bounded log-logistic distributions assumed to be underlying daily offer prices, using information available real-time. The relation between data and parameters is dynamically modeled using economic regimes (characterizing market conditions) and error terms (accounting for customer feedback). Given the parametric approximations of price distributions, acceptance probabilities are estimated using a closed-form mathematical expression, which is used to determine the price yielding a desired quota. The approach is implemented in the MinneTAC agent and tested against a price-following product pricing method in the TAC SCM game. Performance significantly improves; more customer orders are obtained against higher prices and profits more than double.