Most multi-agent systems which have applied ontology design focus on the use of domain ontology. In contrast with domain ontology which characterizes the domain knowledge where the task is performed, task ontology characterizes the computational architecture of a knowledge-based system which performs a task. To establish the task ontology based on KB’s framework, we propose the methodology of KB’s (Knowledge Beads) for automated negotiation. Here the methodology is defined as a set of procedures employed by a discipline that is used in the negotiation life cycle. The discipline is determined on the function making use of the knowledge.
Fig. 1. Methodology of KB’s for automated negotiation
Fig. 1 shows how Negotiation Knowledge and Contextual e-Commerce Knowledge are used respectively for assisting the user to create a RFQ, and for the automated negotiation process. At the end of the process, log files are generated and added to the Contextual e-Commerce Knowledge database.
To our knowledge, most current automated negotiation systems lack the ability of specifying the explicit use of knowledge in a systematic way, thus lack an efficient knowledge assisted automatic negotiation process. For this purpose, we define meta-KB as a meta-object for describing the procedural knowledge necessary to perform a certain task in the e-Procurement context. It contains the meta-knowledge about KB’s, which is knowledge about knowledge. The function which makes use of the meta-KB determines its discipline. Like an ordinary KB, a meta-KB contains attributes forming the knowledge. The attributes are either inherited from an existing KB or defined especially for the specific function, depending on the meta-KB’s discipline. For each attribute, the meta-KB specifies how the attribute value is obtained. The meta-KB for evaluation of a supplier inherits the attributes from the KB comprising knowledge about a supplier’s credit as shown in Table 1. It is illustrated in the following table. The tag ‘Meta-KB’ denotes it a meta-KB, and the use of the meta-KB is declared at the top of the table. It then specifies from which KB template that the meta-KB inherits its attributes. The value of Base Reputation is input from a Negotiation Expert manually. The attribute Number of Contracts Made has a returned function value evaluated on the negotiation log. The function is denoted by f in the table. The attribute Average Utility also has a returned function value evaluated on the negotiation log. The function is denoted by g in the table. The negotiation log is containing all the past successful deals committed with the particular supplier. Weights associated with attributes are also inherited from the supplier credit profile, which are not shown here.
Table 1.1. Meta-KB for supplier evaluation
b. Knowledge Management Life Cycle
Knowledge management is performed throughout the proposed negotiation life cycle. Correspondingly, we propose the concept of knowledge management life cycle in automated negotiation. Our proposed knowledge management life cycle aims at facilitating the creation of negotiation expertise learning in automated negotiation. It comprises the following three phases: knowledge creation, exchanging and use of knowledge, and knowledge evaluation and renewal.
Fig. 2. Knowledge management life cycle
The knowledge creation phase corresponds to the specification and design phase in the proposed negotiation life cycle. It executes knowledge management tasks to assist in the specification of negotiation context. Old and existing knowledge which is relevant to the current negotiation context is identified. New knowledge is then created with respect to the procurement requirements and constraints. This phase involves mainly the manipulation of the Contextual e-Commerce Knowledge items, which are represented in
Exchanging and Use of Knowledge
The phase of exchanging and use of knowledge corresponds to both the quotes evaluation and ranking phase and negotiation execution phase in the proposed negotiation life cycle. The knowledge management task to verify selected knowledge is performed in screening and evaluation phase, which is the core model of the quotes evaluation and ranking phase. The task to learn and apply negotiation knowledge from the history is performed in the negotiation execution phase.
Knowledge Evaluation and Renewal
The knowledge evaluation and renewal phase corresponds to the post-negotiation procession phase in the proposed negotiation life cycle. The knowledge management tasks mainly involve the capture and organization of knowledge, and the production of updated knowledge. This last phase involves re-evaluating old knowledge used in the past and using the evaluation result to create updated knowledge.