Practical Issues in Temporal Difference Learning
Machine Learning
TD-Gammon, a self-teaching backgammon program, achieves master-level play
Neural Computation
Model-based average reward reinforcement learning
Artificial Intelligence
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Computers play the beer game: can artificial agents manage supply chains?
Decision Support Systems - Special issue: Formal modeling and electronic commerce
Control of exploitation-exploration meta-parameter in reinforcement learning
Neural Networks - Computational models of neuromodulation
Applications of the self-organising map to reinforcement learning
Neural Networks - New developments in self-organizing maps
Dynamic Programming
Agent-based demand forecast in multi-echelon supply chain
Decision Support Systems
Beer game order policy optimization under changing customer demand
Decision Support Systems
Supply chain integration in vendor-managed inventory
Decision Support Systems
A study on inventory replenishment policies in a two-echelon supply chain system
Computers and Industrial Engineering - Special issue: Logistics and supply chain management
Simulation-based optimization of process control policies for inventory management in supply chains
Automatica (Journal of IFAC)
Accessing information sharing and information quality in supply chain management
Decision Support Systems
Adaptive state space partitioning for reinforcement learning
Engineering Applications of Artificial Intelligence
Constraint-directed business simulation for supporting game-based problem-based learning
MTDL '09 Proceedings of the first ACM international workshop on Multimedia technologies for distance learning
Neuroevolutionary Inventory Control in Multi-Echelon Systems
ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory
Supply chain formation using agent negotiation
Decision Support Systems
Multi-goal Q-learning of cooperative teams
Expert Systems with Applications: An International Journal
A production-inventory model of imperfect quality products in a three-layer supply chain
Decision Support Systems
Approximate dynamic programming for an inventory problem: Empirical comparison
Computers and Industrial Engineering
Improvement of supply chain efficiency with a computer learning game
AMERICAN-MATH'12/CEA'12 Proceedings of the 6th WSEAS international conference on Computer Engineering and Applications, and Proceedings of the 2012 American conference on Applied Mathematics
Agent learning in autonomic manufacturing execution systems for enterprise networking
Computers and Industrial Engineering
Adaptive learning algorithm of self-organizing teams
Expert Systems with Applications: An International Journal
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A major challenge in supply chain ordering management is the coordination of ordering policies adopted by each level of the chain, so as to minimize inventory costs. This paper describes a new approach to decide on ordering policies of supply chain members in an integrated manner. In the first step supply chain ordering management has been considered as a multi-agent system and formulated as a reinforcement learning (RL) model. In the final step a Q-learning algorithm is proposed to solve the RL model. Results show that the reinforcement learning ordering mechanism (RLOM) is better than two other known algorithms.