JA3. Learning Journal 3¶
The Learning Journal is a tool for self-reflection on the learning process. In addition to completing directed tasks, you should use the Learning Journal to document your activities, record problems you may have encountered and to draft answers for Discussion Forums and Assignments. The Learning Journal should be updated regularly (on a weekly basis), as the learning journals will be assessed by your instructor as part of your Final Grade.
Answer the following questions in your Learning Journal¶
1. Describe what you did. You need to describe what you did and how you did it¶
This was the third week of this course; it was about graphs. I started by trying the self-quiz and then reading what I can from the course material. Unfortunately, this week included graded quizzes in other courses so I was not able to finish all the readings. I later did the discussion assignment about comparing the depth-first search and breadth-first search algorithms. I also did the programming assignment which included analyzing a graph and studying its features such as data structure, cycles, connectedness, and so on.
2. Describe your reactions to what you did¶
Graphs as a topic are interesting. They are also being heavily used in computer science and in other courses I am taking such as artificial intelligence. I am really happy knowing that trees that we learned in previous courses are a special case of graphs and that I am already familiar with some concepts such as graph traversal, depth-first search, and breadth-first search.
3. Describe any feedback you received or any specific interactions you had. Discuss how they were helpful¶
I received an encouraging feedback on both my journal and discussion assignment and praise for my bus-travel example which explains DFS and BFS in a simple way. It is simply a tourist trying to ride all bus routes between two train stations to see as much as possible from the city; I think people liked this example.
4. Describe your feelings and attitudes¶
I was mostly happy. Some of my colleagues wrote an interesting discussion assignments about the differences between DFS and BFS supporting with interesting diagrams. However, I was also upset with the quality of some assignments as it was low.
5. Describe what you learned¶
The week talked about graphs and their properties such as cycles, connectedness, simplicity, degrees of vertices, and so on. I learned about search strategies such as depth-first search and breadth-first search and greedy algorithms. I also learned how to connect those strategies into informed and uninformed contexts resulting in more strategies such as lowest-cost-first, best-first, iterative deepening, and A* search.
I cyclic graph is a graph that contains a cycle, which is a path that starts and ends at the same node. The graph is acyclic if it doesn’t contain any cycles. An acyclic graph is simple if it does not have multiple edges between a pair of nodes as having cycles or multiple edges makes the graph non-simple. A directed graph is a graph where the edges have a direction; that is 1-->2 is different from 2-->1. An undirected graph is a graph where 1--2 and 2--1 are the same; hence, it can be traversed in both directions. A connected graph is a graph where there is a path between every pair of nodes; that is, from any node, you can reach any other node. A weakly connected graph is a directed graph where ignoring the direction of the edges makes it connected. A strongly connected graph is a directed graph where there is a path from every node to every other node.
6. What surprised me or caused me to wonder?¶
I was surprised that a graph with 10 nodes such as the one we analyzed in the programming assignment can have so many paths to follow. I was wondered how much possibilities a relatively bigger graph can have and wether the same techniques that we learned this week can be applied or there are more techniques to learn if a person want to specialize.
7. What happened that felt particularly challenging? Why was it challenging to me?¶
The learning journal was particularly challenging. The first part that requires discussing an employee planning to visit the world and we are tasked to prepare a proper heuristic function and alternative search strategy for the issue. The challenge was that this question seemed partially subjective as it includes a technical part (graph complexity, memory limits, asymptotic complexity, etc), and a problem-related part (client’s preferences, budget, time, etc). I was not sure how to balance between the two parts so I focused on the problem-related part putting some of my assumptions and preferences.
The second part of the assignment was to traverse the path to choose the shortest cheapest route from A-J using A* algorithm. It was easier for me to do this in actual programming using Python rather than manually computing routes and costs which was time-consuming and error-prone. I ended up doing a reference table for all possible routes and costs, and then used it to simulate the process of choosing the next node.
8. What skills and knowledge do I recognize that I am gaining?¶
I am gaining a better understanding of graphs and their properties, the search strategies, and how to apply them in different contexts. Brute force, divide and conquer, and now greedy algorithms are all good skills to be under your belt to solve day-to-day software engineering problems.
9. What am I realizing about myself as a learner?¶
I am realizing that I am more of a visual learner. I like to see diagrams and examples to understand the concepts better. Understanding graphs traversal and search strategies was hard for me using textual content alone so I looked for videos and images that led to me understanding the concepts better.
10. In what ways am I able to apply the ideas and concepts gained to my own experience?¶
A big chunk of problems we face in a typical day as a software engineer can be modeled as graphs. For example, selecting the best recommended product, optimizing friends suggestions, and even finding the best value for money in a basket of products. All these can be modeled as graphs and solved using the techniques we learned this week.