wip: adding basis for caspar #6648
Conversation
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## master #6648 +/- ##
============================================
- Coverage 29.15% 29.12% -0.03%
- Complexity 15454 15472 +18
============================================
Files 2876 2884 +8
Lines 280447 280838 +391
Branches 49383 49419 +36
============================================
+ Hits 81758 81792 +34
- Misses 193203 193558 +355
- Partials 5486 5488 +2 ☔ View full report in Codecov by Sentry. |
![github-advanced-security[bot]](https://avatars.githubusercontent.com/in/57789?s=60&v=4){kind=small}
| * @param gameState The current game state | ||
| * @return A strategic value score | ||
| */ | ||
| private double calculateStrategicValue(Hex hex, GameState gameState) { |
Check notice
Code scanning / CodeQL
Useless parameter Note
| * @param gameState The current game state | ||
| * @return A strategic value score | ||
| */ | ||
| private double calculateStrategicValue(Hex hex, GameState gameState) { |
Check notice
Code scanning / CodeQL
Useless parameter Note
| List<TacticalObjective> sortedObjectives = objectives.values().stream() | ||
| .sorted((a, b) -> Double.compare(b.getPriority(), a.getPriority())) | ||
| .toList(); |
Check notice
Code scanning / CodeQL
Unread local variable Note
| * @param availableObjectives Available objectives | ||
| * @return The best matching objective, or null if none | ||
| */ | ||
| private TacticalObjective findBestObjective(Formation formation, List<TacticalObjective> availableObjectives) { |
Check notice
Code scanning / CodeQL
Useless parameter Note
| return longRangePaths; | ||
| } | ||
|
|
||
| protected Map<Integer, List<MovePath>> getUnitPaths() { | ||
| public Map<Integer, List<MovePath>> getUnitPaths() { |
Check notice
Code scanning / CodeQL
Exposing internal representation Note
Scoppio
added
Princess/AI
PACAR
| * @param gameState The current game state | ||
| * @return The selected firing solution | ||
| */ | ||
| public FiringPlan determineFiringPlan(Entity unit, List<Entity> possibleTargets, GameState gameState) { |
Check notice
Code scanning / CodeQL
Useless parameter Note
| * @param adjacent List of adjacent valid coordinates | ||
| * @return Score value (higher is better) | ||
| */ | ||
| double scorePosition(Coords coord, List<Coords> adjacent); |
Check notice
Code scanning / CodeQL
Useless parameter Note
| NeuralNetwork model = trainModel(modelName, level, dataset, architecture, epochs, batchSize); | ||
| model.saveModel(modelName, level); | ||
| } catch (Exception e) { | ||
| logger.error(e, "Failed to train model for {}", level); |
Check warning
Code scanning / CodeQL
Unused format argument Warning
| double[][][] weights = new double[architecture.getLayerCount() - 1][][]; | ||
| double[][] biases = new double[architecture.getLayerCount() - 1][]; | ||
|
|
||
| Random random = new Random(level.ordinal() * 1000 + architecture.hashCode()); |
Check warning
Code scanning / CodeQL
Result of multiplication cast to wider type Warning
| } | ||
|
|
||
|
|
||
| this.epochs = Integer.parseInt(args[0]); |
Check notice
Code scanning / CodeQL
Missing catch of NumberFormatException Note
| * @param depth Maximum path generation depth | ||
| * @return List of generated paths | ||
| */ | ||
| List<MovePath> generatePaths(Entity unit, GameState gameState, double depth); |
Check notice
Code scanning / CodeQL
Useless parameter Note
| * @param depth Maximum path generation depth | ||
| * @return List of generated paths | ||
| */ | ||
| List<MovePath> generatePaths(Entity unit, GameState gameState, double depth); |
Check notice
Code scanning / CodeQL
Useless parameter Note
No description provided.