Added citation to the report

report/src/references.bib

@@ -1,3 +1,18 @@
+@book{russel2010,
+  added-at  = {2020-02-01T18:23:11.000+0100},
+  author    = {Russell, Stuart and Norvig, Peter},
+  biburl    = {https://www.bibsonomy.org/bibtex/20533b732950d1c5ab4ac12d4f32fe637/mialhoma},
+  edition   = 3,
+  interhash = {53908a52dd4c6c8e39f93f4ffc8341be},
+  intrahash = {0533b732950d1c5ab4ac12d4f32fe637},
+  keywords  = {ties4530},
+  publisher = {Prentice Hall},
+  timestamp = {2020-02-01T18:23:11.000+0100},
+  title     = {Artificial Intelligence: A Modern Approach},
+  year      = 2010
+}
+
+
 @inproceedings{planutils,
   title        = {PLANUTILS: Bringing Planning to the Masses},
   author       = {Muise, Christian and Pommerening, Florian and Seipp, Jendrik and Katz, Michael},

report/src/sections/introduction.tex

@@ -1,6 +1,6 @@
 \section{Introduction}
 
-In artificial intelligence, an agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators. However, such a broad definition is not particularly useful. Much more interesting is the idea of an agent (or system of agents) that operates with the objective to maximize its expected performance measure given its available knowledge and resources. Still, intelligent agents need not only to be rational, but also autonomous, that is, they should act independently by external control and learn to compensate for their partial or incorrect prior knowledge of the world.
+In artificial intelligence, an agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators \parencite{russel2010}. However, such a broad definition is not particularly useful. Much more interesting is the idea of an agent (or system of agents) that operates with the objective to maximize its expected performance measure given its available knowledge and resources. Still, intelligent agents need not only to be rational, but also autonomous, that is, they should act independently by external control and learn to compensate for their partial or incorrect prior knowledge of the world.
 
 Based on these ideas, the hereby presented project involved creating an autonomous and rational (multi-) agent system to play the game of Deliveroo. The task is inspired by the real-world problem of courier services, where parcels have to be delivered to different locations in a timely and efficient manner. In more details, the game is played on a two-dimensional map, where parcels are randomly generated and spawns with a random reward value that may decay over time. The objective of the agents is to collect and deliver parcels to the designated delivery locations in order to maximize their total reward.