In this paper, we employ the fuzzy repertory table technique to acquire the necessary domain knowledge for software agents to act as sellers and buyers using a bilateral, multi-issue negotiation model that can achieve optimal results in semi-competitive environments. In this context, the seller’s domain knowledge that need to be acquired is the rewards associated with the products and restrictions attached to their purchase. The buyer’s domain knowledge that is acquired is the requirements and preferences on the desired products. The knowledge acquisition methods we develop involve constructing three fuzzy repertory tables and their associated distictions matrixes. The first two are employed to acquire the seller agent’s domain knowledge; and the third one is used, together with an inductive machine learning algorithm, to acquire the domain knowledge for the buyer agent.