Developed and Enhanced Activity Selection Algorithms

• Day: 2024-04-17
• Time: 00:10 to 03:00
• Project: Dev
• Workspace: WP 2: Operational
• Status: In Progress
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Activity Selection, Algorithm Design, Verbose Output, Visualization, Python, Education

Description

Session Goal: The session aimed to design and implement various activity selection algorithms using different techniques, including backtracking, dynamic programming, and greedy approaches.

Key Activities:

• Mapped exercises to Chapter 5 of Kleinberg and Tardos’s Algorithm Design, focusing on divide and conquer techniques.
• Implemented a verbose version of the BacktrackingSelector class to provide a clear visual representation of the decision-making process.
• Enhanced the DynamicProgrammingSelector class with verbose outputs to illustrate the dynamic programming algorithm’s decision-making.
• Developed a verbose implementation of the GreedySelector class to demonstrate the greedy algorithm’s decision-making process.
• Utilized [[matplotlib]] for visualizing the activity selection process on a timeline.

Achievements:

• Successfully implemented and enhanced three versions of the activity selection algorithm, providing educational insights through verbose outputs.
• Created visualizations to aid in understanding the algorithm’s operations.

Pending Tasks:

• Further testing and optimization of the implemented algorithms to ensure efficiency and correctness.
• Integration of the visualizations with the algorithm implementations for a comprehensive educational tool.

Evidence

• source_file=2024-04-17.sessions.jsonl, line_number=1, event_count=0, session_id=fa3fd97528a9d41ceda4e5343a00ebb87171979eb763daf9b344a0a18252a7a6
• event_ids: []