A learning-enabled infrastructure for electronic contracting agents
With the vigorous development of electronic commerce these years, many experts and scholars have devoted themselves to various fields of research and application. Of these fields, electronic contracting is a new research topic in great demand. In spite of its promise, electronic contracting involves the standardization of ontology and automation of negotiation, which renders the implementation of electronic contracting difficult. In view of the necessity of electronic contracting, we present a learning-enabled agent-based infrastructure and claim that it will be a solution to the problems encountered during the process of electronic contracting by a variety of evaluations. In this infrastructure, the applications of an agent are viewed as a set of application ontologies, each of which is a combination of a context ontology and a object ontology so that the negotiation context and automation of negotiation can be flexibly integrated in this infrastructure. The infrastructure enables the automation of electronic contracting through a general and automatic communication protocol and provides reusability by the componentization of agents. The infrastructure provides personalized multiattribute evaluation and proposal generation by a mechanism, which is a combination of neural networks and genetic algorithms, in order to enable the automatic negotiation ability at agents.
electronic contracting ontology neural networks genetic algorithms brokering automated negotiation