Two-dimensional learning mechanisms for alliance members in multi-agent supply chains

Cooperative alliances in supply chains have been attracting increasing interests from supply chain management researchers. While learning from experience seems to positively affect the alliance performance in supply chain, there is a lack of an explicit description on learning mechanism for alliance members. Therefore, this paper proposes a two-dimensional learning mechanism for alliance members in multi-agent supply chains. Intelligent agents with learning abilities are modeled as member firms, in which the learning structures based on reinforcement learning are defined The validity of such framework is established by simulating an example learning application using the simplified proposed learning mechanism in a supply chain alliance.