aiplan4eu/unified-planning
Jan 2025 – Jul 2025
5 Months active
Languages Used
PythonPddlYAML
Technical Skills
AI PlanningAlgorithm DesignBackend DevelopmentBug FixDebuggingPDDL
Luca Framba
PROFILE
Luca Framba
Francesco Rambaldi contributed to the aiplan4eu/unified-planning repository by engineering robust enhancements to planning pipelines and validation systems. He improved the PDDL parser and reader using Python, focusing on encoding handling and error feedback to support diverse file formats and prevent runtime failures. His work included extending the ENHSP planner to support continuous effects and events, refining plan output for downstream integration, and modernizing CI/CD workflows with GitHub Actions and Ubuntu 22.04. Through targeted bug fixes, strict validation, and expanded test coverage, Francesco delivered maintainable, reliable backend components that strengthened plan quality assessment and improved the reliability of automated planning workflows.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
17Total
Bugs
5
Commits
17
Features
5
Lines of code
616
Activity Months5
Your Network
25 people
Work History
July 2025
2 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for aiplan4eu/unified-planning: Delivered ENHSP Planner enhancements to extend capabilities and cleaned plan outputs; fixed a critical internal engine issue; and strengthened integration with pddl_anytime_planner for parsing control. The changes broaden domain modeling, improve reliability, and deliver cleaner plans for downstream systems.
2 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for aiplan4eu/unified-planning: Delivered ENHSP Planner enhancements to extend capabilities and cleaned plan outputs; fixed a critical internal engine issue; and strengthened integration with pddl_anytime_planner for parsing control. The changes broaden domain modeling, improve reliability, and deliver cleaner plans for downstream systems.
July 2025
May 2025
4 Commits • 1 Features
May 1, 2025May 2025 — Delivered core reliability and encoding robustness enhancements in aiplan4eu/unified-planning. Key outcomes include stricter UPState validation with better error feedback to catch invalid fluent assignments early, plus targeted test coverage; and PDDL encoding robustness by standardizing UTF-8 with BOM across the parser, reader, and IO utilities to handle diverse file encodings. These improvements reduce runtime errors, improve debugging, and enable smoother integration with external workflows, reflecting strong Python engineering, test-driven development, and encoding/IO handling skills.
May 2025
4 Commits • 1 Features
May 1, 2025May 2025 — Delivered core reliability and encoding robustness enhancements in aiplan4eu/unified-planning. Key outcomes include stricter UPState validation with better error feedback to catch invalid fluent assignments early, plus targeted test coverage; and PDDL encoding robustness by standardizing UTF-8 with BOM across the parser, reader, and IO utilities to handle diverse file encodings. These improvements reduce runtime errors, improve debugging, and enable smoother integration with external workflows, reflecting strong Python engineering, test-driven development, and encoding/IO handling skills.
April 2025
5 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for aiplan4eu/unified-planning focusing on reliability and maintainability gains from PDDL parser robustness work and CI modernization. Delivered concrete improvements to the PDDLReader correctness, better handling of forall constructs, and an Ubuntu 22.04 CI upgrade enabling more reliable test runs and faster feedback loops, reducing planning pipeline risk.
5 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for aiplan4eu/unified-planning focusing on reliability and maintainability gains from PDDL parser robustness work and CI modernization. Delivered concrete improvements to the PDDLReader correctness, better handling of forall constructs, and an Ubuntu 22.04 CI upgrade enabling more reliable test runs and faster feedback loops, reducing planning pipeline risk.
April 2025
February 2025
1 Commits
Feb 1, 2025February 2025 monthly summary for aiplan4eu/unified-planning. Focused on stabilizing the plan validation engine and preventing crashes in edge cases. No new features delivered this month; primary work centered on robustness, bug fixes, and code quality. Key outcomes include a crash prevention in TimeTriggeredPlanValidator for empty plans, with duration 0 for empty inputs, improving reliability for automated plan validation and downstream pipelines. This work reduces production risk and supports smoother deployments in user-facing workflows.
February 2025
1 Commits
Feb 1, 2025February 2025 monthly summary for aiplan4eu/unified-planning. Focused on stabilizing the plan validation engine and preventing crashes in edge cases. No new features delivered this month; primary work centered on robustness, bug fixes, and code quality. Key outcomes include a crash prevention in TimeTriggeredPlanValidator for empty plans, with duration 0 for empty inputs, improving reliability for automated plan validation and downstream pipelines. This work reduces production risk and supports smoother deployments in user-facing workflows.
January 2025
5 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for aiplan4eu/unified-planning. This period focused on robustness, measurable plan quality, and test reliability to accelerate planning pipelines and ensure dependable results in production. Key improvements reduce edge-case failures and enable quantitative assessment of generated plans, driving better decision-making and deployment confidence.
5 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for aiplan4eu/unified-planning. This period focused on robustness, measurable plan quality, and test reliability to accelerate planning pipelines and ensure dependable results in production. Key improvements reduce edge-case failures and enable quantitative assessment of generated plans, driving better decision-making and deployment confidence.
January 2025
Activity
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Quality Metrics
Correctness91.8%
Maintainability91.8%
Architecture90.6%
Performance85.8%
AI Usage21.2%
Skills & Technologies
Programming Languages
PddlPythonYAML
Technical Skills
AI PlanningAction RepresentationAlgorithm DesignBackend DevelopmentBug FixBug FixingCI/CDDebuggingEncodingEncoding HandlingError HandlingException HandlingFile HandlingFile I/OGitHub Actions
Repositories Contributed To
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