The paper evaluates the eectiveness of learning for speeding up the solution of constraint satisfaction problems. It extends previous work (Dechter 1990) by introducing a new and ...
Despite the long history of classical planning, there has been very little comparative analysis of the performance tradeoffs offered by the multitude of existing planning algorith...
This article describes a new system for induction of oblique decision trees. This system, OC1, combines deterministic hill-climbing with two forms of randomization to nd a good ob...
This paper describes how meta-level theories are used for analytic learning in M U L T I - T A C . M U L T I - T A C operationalizes generic heuristics for constraint-satisfaction...
Abstract. While traditional technology acceptance models concentrate on relationships between usefulness and acceptance, they leave unresolved the questions about why a certain tec...