Lecture 2.3

Logistics

• Fix YAML files by tomorrow at midnight. The YAML file is your group.
• Deadline for project proposal moved to Monday.
• Quiz
• GitHub Classroom

Learning Objectives

• Understand the general behavior of informed search algorithms
• Describe the specific behavior of the Greedy Best-First and A\* Search algorithm
• Be able to define the role of a heuristic
• Name and define criteria for heuristics:
  • Admissibility
  • Consistency
• (maybe next time) Be able to check whether a heuristic is admissible or consistent

Warm-Up

Q: What’s the difference between an informed and uninformed search algorithm?

A:

Another Warm-Up

Q: What’s a heuristic? Have you used this term before?

A:

Informed Search

(find-file "./slides/informed_search_intro.pdf")

Greedy Best-First Search

(find-file "./slides/gbfs_a_star.pdf")

A-Star Search

(find-file "./slides/gbfs_a_star.pdf")

Heuristics

• A heuristic guides the search process “top-down”
• Often provides “privileged” information (info that can’t be found just by expanding nodes)

Evaluating Heuristics

(find-file "./slides/admissibility_consistency_v2.pdf")

1. Admissibility

2. Consistency

Qualitative Comparison

How do BFS, DFS, Dijkstra, and A* compare in three environments?

What do we think the colors represent?

Search Variants

A_StarVariants

(find-file "./slides_for_conversion/pdf/a_star_applications.pdf")

Bidirectional Search

Beam Search

Weighted A*

Iterative Deepening Search

Search Summary

<./slides/search_summary.pdf>

(find-file "./slides/search_summary.pdf")

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