METHODS FOR AUTOMATED REASONING

CONTENT:

• Introduction: computational theory and complexity.
• Automatic reasoning.
• Automatic reasoning principles.
• Inference engines.
• Propositional automatic reasoning.
• Model-based automatic reasoning.
• Non-monotonic reasoning.
• Constraint reasoning.
• Constraint satisfaction.
• Constraint Nets, properties.
• Local and global consistency.
• Filtering algorithms, heuristics.
• Inteligent backtracking.
• Constraint optimization.
• Valued problems, semi-ring.
• Branch and Bound, filtering.
• Directional consistency.

DESCRIPTION:

The aim of this course is to provide a complete overview about the algorithmic methods for automatic reasoning, pointing out their abilities and limitations.

Responsable/s

• ESCALADA IMAZ, GONZALO
• LARROSA BONDIA, FRANCISCO JAVIER
• MESEGUER GONZALEZ, PEDRO