What do we learn in class :

Today we were learning about Uninformed Search, Problem-solving agents and reviewing topics about state spaces since this course has a very strong connection with Analysis of Algorithm, therefore we tried to get over those once again, unfortunately, most of us forget about the topics so our lecture needs to repeat few things before we continue.

In public solving agents, there are 6 steps.

• States 
• Starting  
• Actions 
• Transition Model 
• Goal test 
• Path cost

From the wording itself, it is clear that each state represents the steps sequentially before any algorithm started to run.

Before searching, we need to know the nodes first and each node consists of these following :

• State 
• Parent node 
• Action 
• Path cost 
• depth 

Now the different types of uninformed searching are BFS, DFS, UCS, DLS and IDS, different types of search have different time complexity and different ways to implement depends on different situations.

Lastly, we were given a small task for us to finish whenever we want since it will not be marked, but we manage to finish it before class, therefore, we could discuss the results afterwards.

My obstacles and challenges:

It is very difficult for me to understand the whole search strategies with their complexity in one day. So it might need more time in order to understand the whole topics on day 2.