In this paper we address the question of assigning social norms to agents: should we attempt to ascribe social norms to agents that will act in complex dynamic environments, or is...
Almost all the approaches in association rule mining suggested the use of a single minimum support, technique that either rules out all infrequent itemsets or suffers from the bot...
Ioannis N. Kouris, Christos Makris, Athanasios K. ...
This paper adopts the idea of using knowledge gained by various validation sessions over time with a validation technology developed previously. The work is designed to reduce the...
This paper presents new methods for probabilistic belief revision and information fusion. By making use of the principles of optimum entropy (ME-principles), we define a generali...
In our previous research, we investigated the properties of case-based plan recognition with incomplete plan libraries. Incremental construction of plan libraries along with retri...
Current rule base maintenance is wasting refinement and inference performance. There are only few maintenance concepts, which enjoy both (1) formal rule refinement and (2) utili...
We present an algorithm for the inference of context-free graph grammars from examples. The algorithm builds on an earlier system for frequent substructure discovery, and is biase...
We report on our on-going effort to build an adaptive driver support system, Driver AdvocateTM , merging various AI techniques, in particular, agents, ontology, production systems...
Chung Hee Hwang, Noel Massey, Bradford W. Miller, ...
In this paper, we present an experimental methodology and results for a machine learning approach to learning opening strategy in the game of Go, a game for which the best compute...