- Classoom: PSCB 220
- Days: Tuesday & Thursday
- Time: 3:30 - 4:50pm.
- Instructor: Rina Dechter
- Book chapters of "Constraint Processing"
The purpose of this course is to familiarize students with the theory and
techniques of constraint processing, using the constraint network model.
This model offers a natural language for encoding world knowledge in areas
such as scheduling, vision, diagnosis, prediction and design, and it
facilitates many computational tasks relevant to these domains. The
course will focus on techniques for constraint processing. It will cover
search techniques, consistency algorithms and structure based techniques,
and will focus on properties that facilitate efficient solutions.
Extensions will be given into applications such as temporal reasoning,
diagnosis, scheduling, and probabilistic Bayes networks. The constraint
language Eclipse may be used for modelling and solving constraint problems.
The topics covered will be taken from the following list.
- The constraint network model, examples. Graph representations,
Properties of binary networks: equivalence,
the minimal and the projection networks.
- Approximation algorithms: local-consistency vs. global-consistency,
arc and path-consistency, directional-consistency, adaptive-consistency, relational-consistency,
- Backtracking strategies:
Look-ahead schemes: forward-checking, variable and value orderings,
constraint propagation. The Davis-Putnam algorithms.
Look-back schemes: backjumping, constraint learning.
- Combining search and inference; the cycle-cutset scheme.
- Stochastic local search algorithms: SLS, GSAT, WSAT
- Constraint-based tractable classes: row-convexity, tightness, looseness,
implicational and functional constraints, Horn clauses.
- Constraint optimization.
- More topology-based concepts and algorithms: tree-clustering,
- Temporal constraint networks: quantitative, qualitative, and integrated
- Constraint Logic Programming
Homeworks and projects (60%), Final (40%).
There will be weekly homework-assignments, a project, a final.
Subject to changes
- Tu, Chapters 1,2: Introduction: examples
and definitions of Constraint networks.
- Th: Holiday (Yom Kipur).
- Tu, (longer class) Chapter 2: Propertries of Binary networks. Chapter 3: Consistency enforcing algorithms, arc, path and i-consistency
- Th, Chapter 3: continued.
- Tu/Th,Chapter 4: Graph concepts (induced-width), Directional consistency, Adaptive-consistency
- Tu/Th: Chapter 5: Backtracking search, look-ahead methods
- Tu/Th, Chapter 6: Backtracking search, look-back methods
- Tu, Chapter 7: combining seach and inference, the cycle-cutset scheme
- Th: Chapter 8: Stochastic local search
- Tu/Th, Chapter 9: Advanced consistency methods; Relational consistency and bucket-elimination
- Tu/Th, Chapter 10: Tractable constraint languages
- Tu, Chapter 11: Constraint optimization
- Th: Thanksgiving
- Additional topics taken from:
Tree-clustering (Chapter 12), Temporal constraints (Chapter 13), Constraint Programming (Chapter 14)
Resources on the Internet