diff --git a/content/CSE510/CSE510_L26.md b/content/CSE510/CSE510_L26.md
new file mode 100644
index 0000000..77c4190
--- /dev/null
+++ b/content/CSE510/CSE510_L26.md
@@ -0,0 +1,38 @@
+# CSE510 Deep Reinforcement Learning (Lecture 26)
+
+## Continue on Real-World Practical Challenges for RL
+
+### Factored multi-agent RL
+
+- Sample efficiency -> Shared Learning
+- Complexity -> High-Order Factorization
+- Partial Observability -> Communication Learning
+- Sparse reward -> Coordinated Exploration
+
+#### Parameter Sharing vs. Diversity
+
+- Parameter Sharing is critical for deep MARL methods
+- However, agents tend to acquire homogenous behaviors
+- Diversity is essential for exploration and practical tasks
+
+[link to paper: Google Football](https://arxiv.org/pdf/1907.11180)
+
+Schematics of Our Approach: Celebrating Diversity in Shared MARL (CDS)
+
+- In representation, CDS allows MARL to adaptively decide
+when to share learning
+- Encouraging Diversity in Optimization
+
+In optimization, maximizing an information-theoretic objective to achieve identity-aware diversity
+
+$$
+\begin{aligned}
+I^\pi(\tau_T;id)&=H(\tau_t)-H(\tau_T|id)=\mathbbb{E}_{id,\tau_T\sim \pi}\left[\log \frac{p(\tau_T|id)}{p(\tau_T)}\right]\\
+&= \mathbb{E}_{id,\tau}\left[ \log \frac{p(o_0|id)}{p(o_0)}+\sum_{t=0}^{T-1}\log\frac{a_t|\tau_t,id}{p(a_t|\tau_t)}+\log \frac{p(o_{t+1}|\tau_t,a_t,id)}{p(o_{t+1}|\tau_t,a_t)}\right]
+\end{aligned}
+$$
+
+Here: $\sum_{t=0}^{T-1}\log\frac{a_t|\tau_t,id}{p(a_t|\tau_t)}$ represents the action diversity.
+
+$\log \frac{p(o_{t+1}|\tau_t,a_t,id)}{p(o_{t+1}|\tau_t,a_t)}$ represents the observation diversity.
+
diff --git a/content/CSE510/_meta.js b/content/CSE510/_meta.js
index 557e618..13aed33 100644
--- a/content/CSE510/_meta.js
+++ b/content/CSE510/_meta.js
@@ -28,4 +28,5 @@ export default {
     CSE510_L23: "CSE510 Deep Reinforcement Learning (Lecture 23)",
     CSE510_L24: "CSE510 Deep Reinforcement Learning (Lecture 24)",
     CSE510_L25: "CSE510 Deep Reinforcement Learning (Lecture 25)",
+    CSE510_L26: "CSE510 Deep Reinforcement Learning (Lecture 26)",
 }
\ No newline at end of file
diff --git a/distribute/prebuild.sh b/distribute/prebuild.sh
index 54a6d7e..ec49385 100644
--- a/distribute/prebuild.sh
+++ b/distribute/prebuild.sh
@@ -24,6 +24,12 @@ for dir in ./content/*/; do
     # strip the leading path and trailing slash
     base_dir="$(basename "${dir%/}")"
 
+    # explicitly ignore Swap
+    if [ "$base_dir" = "Swap" ]; then
+        echo "Ignoring Swap dir: $dir"
+        continue
+    fi
+
     # check if base_dir is in KEEP_PAGES (space-separated list)
     case " $KEEP_PAGES " in
         *" $base_dir "*) 
@@ -40,6 +46,12 @@ done
 for dir in ./public/*/; do
     base_dir="$(basename "${dir%/}")"
 
+    # explicitly ignore Swap
+    if [ "$base_dir" = "Swap" ]; then
+        echo "Ignoring Swap dir: $dir"
+        continue
+    fi
+    
     case " $KEEP_PAGES " in
         *" $base_dir "*) 
             echo "Keeping public dir: $dir"