Bilateral negotiation is an important aspect of e-commerce to bring satisfactory agreement in business transactions. Though auction-based models are more common currently, they are unable to accommodate tradeoffs between multiple parameters. This makes them inappropriate when trading with intangible goods, like information, expertise and help. We approach e-commerce and negotiation in the context of a distributed multiagent peer help system, I-Help, supporting students in a university course. Personal agents keep models of student preferences and negotiate on their behalf to acquire information resources (help) from other agents. Negotiation is modeled using influence diagram, a decision theoretic tool. Agents create models of their opponents during negotiation, which help them predict better the opponent actions. The experiments show that the proposed approach brings better deals to the agent who uses it. However, if both negotiating agents use this approach, the negotiation fails more often.