Value Function Based Production Scheduling
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
TAC-03: a supply-chain trading competition
AI Magazine
A stochastic programming approach to scheduling in TAC SCM
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Redagent: winner of TAC SCM 2003
ACM SIGecom Exchanges
TacTex-03: a supply chain management agent
ACM SIGecom Exchanges
Controlling a supply chain agent using value-based decomposition
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Strategies in supply chain management for the Trading Agent Competition
Electronic Commerce Research and Applications
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Strategic interactions in the TAC 2003 supply chain tournament
CG'04 Proceedings of the 4th international conference on Computers and Games
Hi-index | 0.00 |
The TAC supply-chain game presents automated trading agents with challenging decision problems, including procurement of supplies across multiple periods using multiattribute negotiations. The procurement process involves substantial uncertainty and competition among multiple agents. Our agent, Deep Maize, generates requests for components based on deviations from a reference inventory trajectory defined by estimated market conditions. It then selects among supplier offers by optimizing a value function over potential inventory profiles. This approach offered strategic flexibility and achieved competitive performance in the TAC-03 tournament.