Agent-based modeling is a powerful tool for systems modeling. Instantiating each domain entity with an agent permits us to capture many aspects of system dynamics and interactions...
This paper examines the induction of classification rules from examples using real-world data. Real-world data is almost always characterized by two features, which are important ...
Acquiring knowledge from the Web to build domain ontologies has become a common practice in the Ontological Engineering field. The vast amount of freely available information allo...
Random problem distributions have played a key role in the study and design of algorithms for constraint satisfaction and Boolean satisfiability, as well as in our understanding o...
In this paper we present pddl+, a planning domain description language for modelling mixed discrete-continuous planning domains. We describe the syntax and modelling style of pddl...