Multiagent Distributed Ontology Learning
Leen‐Kiat Soh · 2002
In this paper, we describe a framework for distributed ontology learning embedded in a multiagent environment. The objective of this framework is to improve communication and understanding among the agents while preserving agent autonomy. Each agent maintains a dictionary for its own experience and a translation table. The dictionary allows the agent to compare and discover relationships between a pair of words or concepts, while the translation table enables the agent to learn and record (a selected portion of) the vocabulary of its neighbors that is useful for the collaboration among the agents. The motivation for this distributed ontology learning is that each agent has its own experience and thus learns its own ontology depending on what it has been exposed to. As a result, different agents may use different words to represent the same experience. When two agents communicate, agent A may not understand what agent B and that hinders collaboration. However, equipped with the distributed ontology learning capabilities, agents are able to evolve independently their own ontological knowledge while maintaining translation tables through learning to help sustain the collaborative effort.