fix: fix unresolved merge conflicts (#185)

* fix: fix unresolved merge conflicts

* docs: fix incorrectly formatted equations

This commit fixes the incorrectly formatted equations. These were broken by the
'remark-lint' extension. The 'remark-math' extension was added to prevent this
behavoir in the future.

* build: pin npm versions

.remarkrc

@@ -1,5 +1,6 @@
 {
   "plugins": [
-    "remark-preset-lint-recommended"
+    "remark-preset-lint-recommended",
+    "remark-math"
   ]
 }

package.json

@@ -45,16 +45,17 @@
     }
   },
   "devDependencies": {
-    "@commitlint/cli": "^17.6.5",
-    "@commitlint/config-conventional": "^17.6.5",
-    "commitizen": "^4.3.0",
-    "cz-conventional-changelog": "^3.3.0",
-    "husky": "^8.0.3",
+    "@commitlint/cli": "17.6.5",
+    "@commitlint/config-conventional": "17.6.5",
+    "commitizen": "4.3.0",
+    "cz-conventional-changelog": "3.3.0",
+    "husky": "8.0.3",
     "lint-staged": "13.2.2",
     "release-please": "github:rickstaa/release-please#add_pytoml_version_warning_ignore_ts",
     "remark": "14.0.3",
     "remark-cli": "11.0.0",
     "remark-lint": "9.1.2",
+    "remark-math": "5.1.1",
     "remark-preset-lint-recommended": "6.1.3",
     "sort-package-json": "2.5.0"
   }

stable_gym/envs/biological/oscillator/README.md

@@ -32,7 +32,7 @@ The agent's goal in the oscillator environment is to act in such a way that one
 The Oscillator environment uses the absolute difference between the reference and the state of interest as the cost function:
 
 $$
-cost = (p\_1 - r\_1)^2
+cost = (p_1 - r_1)^2
 $$
 
 ## Environment step return

stable_gym/envs/biological/oscillator_complicated/README.md

@@ -34,9 +34,9 @@ The agent's goal in the oscillator environment is to act in such a way that one
 
 The Oscillator environment uses the absolute difference between the reference and the state of interest as the cost function:
 
-```python
-cost = np.square(p1 - r1)
-```
+$$
+cost = (p_1 - r_1)^2
+$$
 
 ## Environment step return
 

stable_gym/envs/classic_control/ex3_ekf/README.md

@@ -26,9 +26,9 @@ The agent's goal in the Ex3EKF environment is to act so that the estimator estim
 
 The Ex3EKF environment uses the following cost function:
 
-```python
-cost = np.square(hat_x_1 - x_1) + np.square(hat_x_2 - x_2)
-```
+$$
+cost = (hat_x_1 - x_1)^2 + (hat_x_2 - x_2)^2
+$$
 
 ## Environment step return
 

stable_gym/envs/mujoco/ant_cost/README.md

@@ -17,7 +17,7 @@ The rest of the environment is the same as the original Ant environment. Below,
 The cost function of this environment is designed in such a way that it tries to minimize the error between the Ant's forward velocity and a reference value. The cost function is defined as:
 
 $$
-cost = w\_{forward} \times (x\_{velocity} - x\_{reference\_x\_velocity})^2 + w\_{ctrl} \times c\_{ctrl}
+cost = w_{forward} \times (x_{velocity} - x_{reference\_x\_velocity})^2 + w_{ctrl} \times c_{ctrl}
 $$
 
 ## How to use

stable_gym/envs/mujoco/half_cheetah_cost/README.md

@@ -1,11 +1,7 @@
 # HalfCheetahCost gymnasium environment
 
 <div align="center">
-<<<<<<< HEAD
     <img src="https://github.com/rickstaa/stable-gym/assets/17570430/44360980-3ad1-40e9-863e-3417ed3aa4c8" alt="Half Cheetah Cost" width="200px">
-=======
-    <img src="https://github.com/rickstaa/stable-gym/assets/17570430/44360980-3ad1-40e9-863e-3417ed3aa4c8" alt="Half Cheetah" width="200px">
->>>>>>> main
 </div>
 </br>
 
@@ -21,7 +17,7 @@ The rest of the environment is the same as the original HalfCheetah environment.
 The cost function of this environment is designed in such a way that it tries to minimize the error between the HalfCheetah's forward velocity and a reference value. The cost function is defined as:
 
 $$
-cost = w\_{forward} \times (x\_{velocity} - x\_{reference\_x\_velocity})^2 + w\_{ctrl} \times c\_{ctrl}
+cost = w_{forward} \times (x_{velocity} - x_{reference\_x\_velocity})^2 + w_{ctrl} \times c_{ctrl}
 $$
 
 ## How to use

stable_gym/envs/mujoco/swimmer_cost/README.md

@@ -16,7 +16,7 @@ The rest of the environment is the same as the original Swimmer environment. Bel
 The cost function of this environment is designed in such a way that it tries to minimize the error between the Swimmer's forward velocity and a reference value. The cost function is defined as:
 
 $$
-cost = w\_{forward} \times (x\_{velocity} - x\_{reference\_x\_velocity})^2 + w\_{ctrl} \times c\_{ctrl}
+cost = w_{forward} \times (x_{velocity} - x_{reference\_x\_velocity})^2 + w_{ctrl} \times c_{ctrl}
 $$
 
 ## How to use