Attribute-based interactions in agent societies for adaptive plan selection
Muhammad Kamran Iftikhar, Abdul Haseeb · International Conference on Artificial Intelligence · 2009
Collaboration in a society of agents plays a significant role for the overall society to function in an effective manner in reaching its desired goals. Such inter-entity interactions to achieve society goals require prediction of behavior of other entities and an adaptive interaction plan selection and conflict avoidance mechanism to reach local/agent-level- and global/society-level-goals. Earlier works have assumed a priori knowledge and classification of entities and their attributes in a society for selection of a best plan; we consider such assumptions too restrictive and propose an attribute-based adaptive plan selection infrastructure for agents in a society where agents possess minimum knowledge of their surrounding agents. Furthermore we consider attribute rating mechanism for plan conflict resolution.