From e6bc9f8417ddaae1061d6d23d830dbd801871150 Mon Sep 17 00:00:00 2001
From: Jan Grewe <jan.grewe@g-node.org>
Date: Sun, 13 Jan 2019 11:58:33 +0100
Subject: [PATCH] [project random walk] improve text, some hints for plotting

---
 projects/project_random_walk/random_walk.tex | 20 +++++++++++---------
 1 file changed, 11 insertions(+), 9 deletions(-)

diff --git a/projects/project_random_walk/random_walk.tex b/projects/project_random_walk/random_walk.tex
index db0fb84..0748e6a 100644
--- a/projects/project_random_walk/random_walk.tex
+++ b/projects/project_random_walk/random_walk.tex
@@ -13,12 +13,13 @@
 %%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
 \section*{Random walk with memory.}
 
-Some animals perform a random walk when searching for food. In some
-cases this random walk is not completely random. In fact, sometimes
-there is some memory involved. Whenever there is a positive gradient
-in food gain between successive steps the animal will continue in the
-very same direction as before. When the next step leads to a decrease
-in food gain the animal switches back to a random walk.
+The movement pattern of some animals can be described as a random walk when
+searching for food. In some cases this random walk is not completely
+random. In fact, sometimes there is some memory involved. Whenever
+there is a positive gradient in food gain between successive steps the
+animal will continue in the very same direction as in the step before. When the
+next step leads to a decrease in food gain the animal switches back to
+a random walk and changes directions randomly.
 
 
 \begin{questions}
@@ -28,8 +29,8 @@ in food gain the animal switches back to a random walk.
   food sources (Gaussian blotches of food).
   
   \begin{parts}
-    \part{} Create a plot of the world.\\[0.5ex]
-    \part{} Create a model animal that performs a pure random walk. The
+    \part{} Create a plot of the world using \code{imshow}.\\[0.5ex]
+    \part{} Create a model animal (agent) that performs a pure random walk. The
     agent can walk in eight different directions (the cardinal and
     diagonal directions) with a stepsize of 10\,cm
     (approximately). Let the agent start at a random location in the
@@ -37,7 +38,7 @@ in food gain the animal switches back to a random walk.
     disappears from the world, of course). If the agent bumps into the
     borders of the world choose a different direction.\\[0.5ex]
     \part{} Plot a typical example walk. (You can also make an animation
-    with MATLAB)\\[0.5ex]
+    with MATLAB, see plotting chapter in the script).\\[0.5ex]
     \part{} Same as above, but create a model animal that has some memory,
     i.e. the direction is kept constant as long as there is a positive
     gradient in the food gain. Otherwise, a random walk is performed.\\[0.5ex]
@@ -46,6 +47,7 @@ in food gain the animal switches back to a random walk.
     appropriate plots and apply statistical methods. You will need to
     run the simulations several times to get a good estimate of the
     neumbers.
+    \part{} Can you think about better search strategies?
   \end{parts}
 \end{questions}