address yuval comments

Author: thowell

mjpc/planners/sample_gradient/planner.cc

@@ -162,7 +162,7 @@ void SampleGradientPlanner::SetState(const State& state) {
                &this->time);
 }
 
-// optimize nominal policy using random sampling
+// optimize nominal policy using random sampling and gradient search
 void SampleGradientPlanner::OptimizePolicy(int horizon, ThreadPool& pool) {
   // if num_trajectory_ has changed, use it in this new iteration.
   // num_trajectory_ might change while this function runs. Keep it constant
@@ -214,7 +214,7 @@ void SampleGradientPlanner::OptimizePolicy(int horizon, ThreadPool& pool) {
   // start timer
   auto policy_update_start = std::chrono::steady_clock::now();
 
-  // sort candidate policies and trajectories by score
+  // initial order for partial sort
   for (int i = 0; i < num_trajectory; i++) {
     trajectory_order[i] = i;
   }
@@ -254,7 +254,7 @@ void SampleGradientPlanner::OptimizePolicy(int horizon, ThreadPool& pool) {
                               times_scratch);
   }
 
-  // improvement: compare nominal to elite average
+  // improvement: compare nominal to winner
   improvement = mju_max(
       trajectory[idx_nominal].total_return - trajectory[winner].total_return,
       0.0);