A New Bottom-Up Plan Recognition Algorithm based on Plan Knowledge Graph

Plan recognition is an important branch in artificial intelligence. It is significant to develop efficient recognition algorithms. Based on plan knowledge graph, this paper presents a new algorithm which provides a more reasonable explanation for the observed actions. It uses the same representation as the plan knowledge graph. It redefined the abstraction, specialization, whole and part relationships between events. The supporting degree is also discussed particularly. At the same time it improves the algorithm. When it comes into being the solution graph, it removes the node with little probability according to the probability and the threshold. In this way, the number of nodes in the solution graph is reduced and the explanations it produces are more reasonable.