Value-driven procurement in the TAC supply chain game
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.