Multi-agent planning with confidentiality

ABSTRACT

Distributed planning has seen a wide range of techniques aiming to address problems such as distributed plan formation and distributed plan execution. Common to these techniques is the notion of Multi-Agent Planning (MAP) as a combination of planning and coordination by de Weerdt et al. [2]. Among the three types of MAP problems summarised by Durfee [3], distributed planning for distributed plans is considered to be the most challenging. The key issue to tackle is the plan merging, which concerns about resolving potential conflicts (negative interactions) between individual plans (sequences of actions) of the agents. A more complex version of the problem that has many real world examples, is that where agents need to maintain confidential information such as private knowledge, and/or do not wish to expose their individual plans. Such confidentiality constraints may make the central/direct analysis of action interactions impossible. This paper focuses on the task of distributed planning for distributed plans with confidentiality.

REFERENCES

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INDEX TERMS

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

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Coherence and coordination
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Plan execution, formation, and generation
  I.6 SIMULATION AND MODELING
      I.6.4 Model Validation and Analysis
      I.6.5 Model Development
          Subjects: Modeling methodologies

General Terms:
Algorithms, Design, Management, Performance