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Constraint Satisfaction Planning(CSP)
Planning approach that simultaneously satisfies multiple constraints while optimizing objectives
In 30 seconds
- What
- Simultaneously satisfies multiple hard and soft constraints while exploring solution space, using constraint propagation to eliminate infeasible options and resolve conflicts.
- When to use
- Complex scheduling or resource allocation where many requirements compete, feasibility matters as much as optimization, and trade-offs between constraints need explicit handling.
- Watch out
- Computational cost grows exponentially with constraint count; poorly ordered constraint checking can waste cycles exploring dead-end branches before backtracking.
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Constraint Satisfaction Planning: Overview
Planning approach that simultaneously satisfies multiple constraints while optimizing objectives
- Multi-constraint optimization
- Feasibility checking
- Conflict resolution
- Trade-off analysis
- Solution space exploration
- Constraint propagation
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References
The papers, specifications, and repositories this pattern is based on.
- Dechter, R. Constraint Processing. Morgan Kaufmann
- Publisher
- Rossi, van Beek, Walsh. Handbook of Constraint Programming
- Mackworth, A.K. Arc consistency foundations
- Minton, S. et al. Min-Conflicts heuristic for CSPs
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