Developing dynamic strategies for multi-issue automated contracting in the agent based commercial grid

Multiple-issue negotiations between autonomous software agents allow the alignment of resource consumers' demand profiles and the specific service capabilities of resource providers. To address the inefficiencies of negotiations on imperfect markets, the negotiation model suggested here includes both self-interested negotiations driven by a heuristic strategy and a joint-gains approach to win/win-negotiations. The market based grid service allocation mechanism is based on negotiating agents that are aware oj their environment and leverage strategically relevant knowledge to maximize utility. The "GeneLab " simulation environment uses a genetic algorithm to find strong negotiation strategies and suitable knowledge processing rules.