Using decision trees for agent modelling: A study on resolving conflicting predictions

Bark Cheung Chiu, Geoffrey I. Webb, Zijian Zheng

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review


Input-Output Agent Modelling (IOAM) is an approach to modelling an agent in terms of relationships. between the inputs and outputs of the cognitive system. This approach, together with a leading inductive learning algorithm, C4.5, has been adopted to build a subtraction skill modeller, C4.5-IOAM. It models agents' competencies with a set of decision trees. C4.5-IOAM makes no prediction when predictions from different decision trees are contradictory. This paper proposes three techniques for resolving such situations. Two techniques involve selecting the more reliable prediction from a set of competing predictions using a tree quality measure and a leaf quality measure. The other technique merges multiple decision trees into a single tree. This has the additional advantage of producing more comprehensible models. Experimental results, in the domain of modelling elementary subtraction skills, showed that the tree quality and the leaf quality of a decision path provided valuable references for resolving contradicting predictions and a single tree model representation performed nearly equally well to the multi-tree model representation.

Original languageEnglish
Title of host publicationAdvanced Topics in Artificial Intelligence - 10th Australian Joint Conference on Artificial Intelligence, AI 1997, Proceedings
EditorsAbdul Sattar
Number of pages10
ISBN (Print)3540637974, 9783540637974
Publication statusPublished - 1 Jan 1997
Externally publishedYes
EventAustralasian Joint Conference on Artificial Intelligence 1997 - Perth, Australia
Duration: 30 Nov 19974 Dec 1997
Conference number: 10th (Proceedings),center%20in%20Providence%2C%20Rhode%20Island.&text=The%20Hall%20of%20Champions%20was,of%20classic%20games%20of%20strategy.

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceAustralasian Joint Conference on Artificial Intelligence 1997
Abbreviated titleAI 1997
Internet address

Cite this