A Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments

The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality but also with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems (DBEs), as well as related services like open-id, trust management, monitors, and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up ONEs that are stable, a basic condition for predictable and reliable business environments. Aiming to build stable DBEs by means of improved collective intelligence, we introduce a model of negotiation-style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor and a novel negotiation-style recommender (NSR). The ecosystem monitor provides hints to the NSR to achieve greater stability of ONE in a DBE. The greater stability provides the small companies with higher predictability and, therefore, better business results. The NSR is implemented with a simulated-annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of ONE populated by Italian companies.