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Adaptive Pathfinding in Partially Observable Dynamic Environments #114
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Copilot reviewed 28 out of 28 changed files in this pull request and generated 2 comments.
| // cost == Double.POSITIVE_INFINITY -> BreakMove(checkingPos, hCost, nodeType, currentFeetY, cost) | ||
| // (currentFeetY - origin.feetY) > player.stepHeight -> ParkourMove(checkingPos, hCost, nodeType, currentFeetY, cost) |
Copilot
AI
Apr 15, 2025
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[nitpick] There is commented-out code for handling special move cases (e.g. BreakMove and ParkourMove). If these are no longer needed, consider removing them to improve code clarity.
| // cost == Double.POSITIVE_INFINITY -> BreakMove(checkingPos, hCost, nodeType, currentFeetY, cost) | |
| // (currentFeetY - origin.feetY) > player.stepHeight -> ParkourMove(checkingPos, hCost, nodeType, currentFeetY, cost) |
Introduce extensive path consistency tests for scenarios with different graph connectivities and blocked nodes using D* Lite. Add graph pruning logic to exclude nodes marked as blocked and enhance debugging utilities for path validation.
Abstracted grid connectivity into reusable methods for cleaner and more flexible code. Enhanced block update listener to skip redundant updates and improved logging clarity. Simplified pathfinding and traversal checks for better maintainability.
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Introducing an algorithm solving adaptive pathfinding in partially observable dynamic environments using spatial partitioning, iterative pathing using Lazy D* Lite and clearance based path refining using Lazy θ* and Catmull Rom splines.
ToDo: