Fix heuristic example and some crefs (#4690)

Author: Chris Elion

com.unity.ml-agents/Runtime/Agent.cs

@@ -98,7 +98,7 @@ public void CopyActions(ActionBuffers actionBuffers)
     /// * <see cref="BehaviorType.InferenceOnly"/>: decisions are always made using the trained
     ///   model specified in the <see cref="BehaviorParameters"/> component.
     /// * <see cref="BehaviorType.HeuristicOnly"/>: when a decision is needed, the agent's
-    ///   <see cref="Heuristic"/> function is called. Your implementation is responsible for
+    ///   <see cref="Heuristic(in ActionBuffers)"/> function is called. Your implementation is responsible for
     ///   providing the appropriate action.
     ///
     /// To trigger an agent decision automatically, you can attach a <see cref="DecisionRequester"/>
@@ -109,7 +109,7 @@ public void CopyActions(ActionBuffers actionBuffers)
     /// can only take an action when it touches the ground, so several frames might elapse between
     /// one decision and the need for the next.
     ///
-    /// Use the <see cref="OnActionReceived(float[])"/> function to implement the actions your agent can take,
+    /// Use the <see cref="OnActionReceived(ActionBuffers)"/> function to implement the actions your agent can take,
     /// such as moving to reach a goal or interacting with its environment.
     ///
     /// When you call <see cref="EndEpisode"/> on an agent or the agent reaches its <see cref="MaxStep"/> count,
@@ -125,7 +125,7 @@ public void CopyActions(ActionBuffers actionBuffers)
     /// only use the [MonoBehaviour.Update] function for cosmetic purposes. If you override the [MonoBehaviour]
     /// methods, [OnEnable()] or [OnDisable()], always call the base Agent class implementations.
     ///
-    /// You can implement the <see cref="Heuristic"/> function to specify agent actions using
+    /// You can implement the <see cref="Heuristic(in ActionBuffers)"/> function to specify agent actions using
     /// your own heuristic algorithm. Implementing a heuristic function can be useful
     /// for debugging. For example, you can use keyboard input to select agent actions in
     /// order to manually control an agent's behavior.
@@ -293,7 +293,7 @@ internal struct AgentParameters
 
         /// <summary>
         /// VectorActuator which is used by default if no other sensors exist on this Agent. This VectorSensor will
-        /// delegate its actions to <see cref="OnActionReceived(float[])"/> by default in order to keep backward compatibility
+        /// delegate its actions to <see cref="OnActionReceived(ActionBuffers)"/> by default in order to keep backward compatibility
         /// with the current behavior of Agent.
         /// </summary>
         IActuator m_VectorActuator;
@@ -630,7 +630,7 @@ public int CompletedEpisodes
         /// Use <see cref="AddReward(float)"/> to incrementally change the reward rather than
         /// overriding it.
         ///
-        /// Typically, you assign rewards in the Agent subclass's <see cref="OnActionReceived(float[])"/>
+        /// Typically, you assign rewards in the Agent subclass's <see cref="OnActionReceived(ActionBuffers)"/>
         /// implementation after carrying out the received action and evaluating its success.
         ///
         /// Rewards are used during reinforcement learning; they are ignored during inference.
@@ -859,11 +859,12 @@ public virtual void Initialize() { }
         /// You can also use the [Input System package], which provides a more flexible and
         /// configurable input system.
         /// <code>
-        ///     public override void Heuristic(ActionBuffers actionsOut)
+        ///     public override void Heuristic(in ActionBuffers actionsOut)
         ///     {
-        ///         actionsOut.ContinuousActions[0] = Input.GetAxis("Horizontal");
-        ///         actionsOut.ContinuousActions[1] = Input.GetKey(KeyCode.Space) ? 1.0f : 0.0f;
-        ///         actionsOut.ContinuousActions[2] = Input.GetAxis("Vertical");
+        ///         var continuousActionsOut = actionsOut.ContinuousActions;
+        ///         continuousActionsOut[0] = Input.GetAxis("Horizontal");
+        ///         continuousActionsOut[1] = Input.GetKey(KeyCode.Space) ? 1.0f : 0.0f;
+        ///         continuousActionsOut[2] = Input.GetAxis("Vertical");
         ///     }
         /// </code>
         /// [Input Manager]: https://docs.unity3d.com/Manual/class-InputManager.html

com.unity.ml-agents/Runtime/Agent.deprecated.cs

@@ -14,7 +14,7 @@ public virtual void CollectDiscreteActionMasks(DiscreteActionMasker actionMasker
         }
 
         /// <summary>
-        /// This method passes in a float array that is to be populated with actions.
+        /// Deprecated, use <see cref="Heuristic(in ActionBuffers)"/> instead.
         /// </summary>
         /// <param name="actionsOut"></param>
         public virtual void Heuristic(float[] actionsOut)
@@ -35,7 +35,7 @@ public virtual void OnActionReceived(float[] vectorAction) { }
         /// <returns>
         /// The last action that was decided by the Agent (or null if no decision has been made).
         /// </returns>
-        /// <seealso cref="OnActionReceived(float[])"/>
+        /// <seealso cref="OnActionReceived(ActionBuffers)"/>
         // [Obsolete("GetAction has been deprecated, please use GetStoredActionBuffers, Or GetStoredDiscreteActions.")]
         public float[] GetAction()
         {