diff --git a/NEWS.md b/NEWS.md
index fdb06c9..2a1b2de 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -6,6 +6,7 @@
 * sample_belief_space() gained method 'trajectories'.
 * simulate_POMDP(): supports not epsilon-greedy policies.
 * observation_matrix() et al. functions are now created with a separate function ending in _function.
+* fixed converged finite-horizon case. It now only returns the converged graph/alpha.
 
 # pomdp 1.0.1 (03/25/2022)
 
diff --git a/R/POMDP.R b/R/POMDP.R
index 739d144..2dc46f4 100644
--- a/R/POMDP.R
+++ b/R/POMDP.R
@@ -455,36 +455,28 @@ print.POMDP <- function(x, ...) {
     stop("x needs to be a solved POMDP. Use solve_POMDP() first.")
 }
 
-.timedependent_POMDP <- function(x) {
+.timedependent_POMDP <- function(x) 
   !is.null(x$horizon) && length(x$horizon) > 1L
-}
+
 
 # get pg and alpha for a epoch
 .get_pg_index <- function(model, epoch) {
-  .solved_POMDP(model)
+  #.solved_POMDP(model)
   
-  if (epoch < 1)
-    stop("Epoch has to be >= 1")
+  epoch <- as.integer(epoch)
+  if(epoch < 1L) stop("Epoch has to be >= 1")
   
-  h <- model$horizon
-  l <- length(model$solution$pg)
+  ### (converged) infinite horizon POMDPs. We ignore epoch.
+  if (length(model$solution$pg) == 1L) return(1L)
   
-  if (epoch > h)
-    stop("POMDP model was only solved for ", h, " epochs!")
+  ### regular epoch for finite/infinite horizon case
+  if (epoch <= length(model$solution$pg)) return(epoch)
   
-  ### (converged) infinite horizon POMDPs
-  if (is.infinite(h))
-    epoch <- 1L
+  if (epoch > sum(model$horizon))
+    stop("POMDP model was only solved for ", sum(model$horizon), " epochs!")
   
-  ### converged finite horizon model
-  else {
-    if (epoch <= h - l)
-      epoch <- 1L
-    else
-      epoch <- epoch - (h - l)
-  }
-  
-  epoch
+  ### converged finite-horizon case return the last (i.e., converged) epoch
+  return(length(model$solution$pg))
 }
 
 .get_pg <-
@@ -494,7 +486,6 @@ print.POMDP <- function(x, ...) {
   function(model, epoch)
     model$solution$alpha[[.get_pg_index(model, epoch)]]
 
-
 #' @rdname POMDP
 #' @export
 O_ <-
diff --git a/R/plot_policy_graph.R b/R/plot_policy_graph.R
index f55360c..fd8b0c6 100644
--- a/R/plot_policy_graph.R
+++ b/R/plot_policy_graph.R
@@ -222,6 +222,8 @@ policy_graph_unconverged <- function(x, belief = NULL, show_belief = TRUE, col =
   pg[["node"]] <- paste0(pg[["epoch"]], "-", pg[["node"]])
   for(o in observations) {
     pg[[o]] <- paste0(pg[["epoch"]] + 1L, "-", pg[[o]])
+    
+    ## these should be NA. Make sure they are
     pg[[o]][pg[["epoch"]] == epochs] <- NA
   }
   
@@ -231,7 +233,7 @@ policy_graph_unconverged <- function(x, belief = NULL, show_belief = TRUE, col =
   else
     initial_pg_node <- reward_node_action(x, belief = belief)$pg_node
   
-  ## remove unused nodes
+  ## remove unreached nodes
   used <- paste0("1-", initial_pg_node)
   for(i in seq(epochs)) {
     used <- append(used, unlist(pg[pg[["epoch"]] == i & pg[["node"]] %in% used, observations]))
diff --git a/R/read_write_pomdp_solve.R b/R/read_write_pomdp_solve.R
index 7dca7c4..018cfe7 100644
--- a/R/read_write_pomdp_solve.R
+++ b/R/read_write_pomdp_solve.R
@@ -149,11 +149,6 @@
   )
   pg <- pg + 1 #index has to start from 1 not 0
   
-  ### FIXME: I am not sure we need this now
-  #if (dim(pg)[2]==1 ) {
-  #  pg <- t(pg)
-  #}
-  
   # renaming the columns and actions
   colnames(pg) <-
     c("node", "action", as.character(model$observations))
diff --git a/R/solve_POMDP.R b/R/solve_POMDP.R
index 0488b52..ccaefd9 100644
--- a/R/solve_POMDP.R
+++ b/R/solve_POMDP.R
@@ -116,8 +116,9 @@
 #' - `converged` did the solution converge?
 #' - `initial_belief` used initial beliefs.
 #' - `total_expected_reward` reward from the initial beliefs.
-#' - `pg`, `initial_pg_node` a list representing the policy graph. A converged solution has
-#' only a single list elements.
+#' - `pg`, `initial_pg_node` a list representing the policy graph. The epochs are 
+#'  the list entries. A converged infinite-horizon solution has
+#' only a single list elements. Finite-horizon solutions may converge early resulting in a shorter list.
 #' - `belief_states` used belief states.
 #' - `alpha` value function as hyperplanes representing the nodes in the policy graph.
 #' - `policy` the policy.
@@ -498,11 +499,23 @@ solve_POMDP <- function(model,
           cat("Convergence: Finite-horizon POMDP converged early at epoch:",
             i  -  1,
             "\n")
-        converged <- i  -  1
+        converged <- TRUE
+        
+        # we only need to keep the first pg element with the graph
+        pg <- tail(pg, n = 1L)
+        alpha <- tail(alpha, n = 1L)
+        
         break
       }
     }
+   
+    ## make transitions in last epoch NA for non converged solutions
+    if (!converged)
+      pg[[1L]][, as.character(model$observations)] <- NA 
     
+    ## order by epoch
+    alpha <- rev(alpha)
+    pg <- rev(pg)
     
     if (method == "grid" &&
         !converged &&
@@ -511,9 +524,6 @@ solve_POMDP <- function(model,
         "The grid method for finite horizon did not converge. The value function and the calculated reward values may not be valid with negative reward in the reward matrix. Use method 'simulate_POMDP()' to estimate the reward or use solution method 'incprune'."
       )
     
-    alpha <- rev(alpha)
-    pg <- rev(pg)
-    
   }
   
   # read belief states if available (method: grid)
diff --git a/man/solve_POMDP.Rd b/man/solve_POMDP.Rd
index aa5071b..8f55161 100644
--- a/man/solve_POMDP.Rd
+++ b/man/solve_POMDP.Rd
@@ -58,8 +58,9 @@ solver output (\code{solver_output}). The solution is a list with elements:
 \item \code{converged} did the solution converge?
 \item \code{initial_belief} used initial beliefs.
 \item \code{total_expected_reward} reward from the initial beliefs.
-\item \code{pg}, \code{initial_pg_node} a list representing the policy graph. A converged solution has
-only a single list elements.
+\item \code{pg}, \code{initial_pg_node} a list representing the policy graph. The epochs are
+the list entries. A converged infinite-horizon solution has
+only a single list elements. Finite-horizon solutions may converge early resulting in a shorter list.
 \item \code{belief_states} used belief states.
 \item \code{alpha} value function as hyperplanes representing the nodes in the policy graph.
 \item \code{policy} the policy.