Add 13 new procedural datasets across 7 categories

New dataset categories: combinatorics, statistics, optimization, and
formal languages. Extended existing algebra, arithmetic, probability,
logic, and graphs packages with complex_advanced, linear_algebra, limits,
number_theory, conditional_probability, set_operations, and job_scheduling.

Each dataset includes config validation, deterministic seeding, custom
scoring, curriculum support, and comprehensive unit tests (92 new tests).

tests/test_knapsack.py

@@ -0,0 +1,70 @@
+import pytest
+
+from reasoning_gym.optimization.knapsack import (
+    KnapsackConfig,
+    KnapsackCurriculum,
+    KnapsackDataset,
+    _solve_knapsack,
+)
+
+
+def test_config_validation():
+    with pytest.raises(AssertionError):
+        config = KnapsackConfig(min_items=1)
+        config.validate()
+
+    with pytest.raises(AssertionError):
+        config = KnapsackConfig(min_items=10, max_items=5)
+        config.validate()
+
+
+def test_deterministic():
+    config = KnapsackConfig(seed=42, size=10)
+    ds1 = KnapsackDataset(config)
+    ds2 = KnapsackDataset(config)
+    for i in range(len(ds1)):
+        assert ds1[i] == ds2[i]
+
+
+def test_item_structure():
+    config = KnapsackConfig(seed=42, size=50)
+    ds = KnapsackDataset(config)
+    for i in range(len(ds)):
+        item = ds[i]
+        assert isinstance(item, dict)
+        assert "question" in item
+        assert "answer" in item
+        assert "metadata" in item
+        assert item["metadata"]["source_dataset"] == "knapsack"
+
+
+def test_answer_correctness():
+    config = KnapsackConfig(seed=42, size=50)
+    ds = KnapsackDataset(config)
+    for i in range(len(ds)):
+        item = ds[i]
+        weights = item["metadata"]["weights"]
+        values = item["metadata"]["values"]
+        capacity = item["metadata"]["capacity"]
+        expected = _solve_knapsack(weights, values, capacity)
+        assert int(item["answer"]) == expected, f"Item {i}: answer mismatch"
+
+
+def test_score_answer():
+    config = KnapsackConfig(seed=42, size=10)
+    ds = KnapsackDataset(config)
+    for i in range(len(ds)):
+        item = ds[i]
+        score = ds.score_answer(item["answer"], item)
+        assert score == 1.0
+
+
+def test_curriculum():
+    curriculum = KnapsackCurriculum()
+    base_value = {"size": 50, "seed": 1}
+    base_cfg = curriculum.generate_configuration(base_value)
+    assert base_cfg.seed == 1
+
+    curriculum.increment_attr_level("item_count")
+    increased_cfg = curriculum.generate_configuration(base_value)
+    assert increased_cfg.max_items >= base_cfg.max_items