A computation environment for automated negotiation: a case study in electronic tourism

ABSTRACT

The automated negotiation topic plays an important role in e-commerce research. However, despite considerable work on automated negotiation, few research efforts have aimed at software engineering facilities such a reuse and flexibility. To address this issue, we propose a novel computation environment for building agents with flexible negotiation strategies to function in various virtual business domains. Regarding the negotiation strategies, some decision taking assistance techniques may be used in group, e.g. rule-based reasoning and techniques to machine learning. Considering the flexibility of acting in various business domains, a specific agent can be programmed to work in as many business domains as necessary, and essentially, it will also be possible to reconfigure the agent's business domains at execution time. All the experiments in this work were idealized in the terms of a tourism negotiation package. Results from these experiments demonstrate effectiveness of our proposal.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Intelligent agents

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Multiagent systems
      I.2.6 Learning

  J. Computer Applications
  J.4 SOCIAL AND BEHAVIORAL SCIENCES
      Subjects: Economics

General Terms:
Economics, Experimentation

Keywords:
agent and multiagent architectures, cognitive models, electronic commerce, trading agents