Using the \texttt{-l} option the user can give a initial LURD to the program.
LURD stands for Left, Up, Right, Down sequence and is a string consisting only
of $l,u,r,d$ characters and it specifies the initial moves to be taken by the
-agent. To achieve this we simple for every character in the lurd update the
+agent. To achieve this we simple for every character in the LURD update the
initial state with the relative product of the transitions belonging to the
correct direction. After that the problem is solved as usual and thus notifying
-the user wether the LURD leads to a solvable state. Note that when the LURD is
+the user whether the LURD leads to a solvable state. Note that when the LURD is
empty the program behaves like there was no LURD given.
\subsection{Evaluation}
knowlegde and the knowledge required to build such a solver is quite big. This
lead to startup problems (which we managed to solve, but lost too much time to it).
-Finally, we feel a bit frustrated that we only finished and tested the reachability of a goal state checking, but did not finish the extraction of solving sequences.
+Finally, we feel a bit frustrated that we only finished and tested the reachability of a goal state checking, but did not finish the extraction of solving sequences. We have a solution for that problem, which shows potential, but still contains bugs.
-% Maybe something about the complexity of the assignment
+\subsubsection{Diviion of work}
+The work was divided evenly in the beginning of the project. When we noticed
+that we did not have enough time to implement two solutions or even a hybrid
+approach we decided to go through with the solution that seemed the most
+doable. In the next phase of the project Alexander did more of the programming
+and Mart more on the report. Cumulatively we spent a lot of time on it.
repositories / mc1516pa.git / blobdiff