Week 1

On our first week class, we were told about the introduction of Intelligent Systems materials especially the basic concept of Artificial Intelligence and Machine Learning. Also the lecturer told us about the rundown or the whole schedule of this course, and ask us to form of group consist of max. 3 persons, and my member’s blog link is down below.

Team Members :
– Alifio Rasendriya Rasyid | 2201798295
– Jason Sianandar | 2201796440

Week 2

On our second week class, the lecturer taught us about Search Strategies in Artificial Intelligence. And those Search Strategies specified into two different techniques which is Uninformed Search and Informed Search.

Uninformed Search is a searching technique that has no additional information about the distance from the current state to the goal.

Informed Search is another technique that has additional information about the estimate distance from the current state to the goal.

The lecturer also give us an exercise about all search techniques to make us more proficient in this Search Strategies topic.

Week 3

On our third week class, the lecturer taught us more specific about the Informed Search. In Informed Search, the algorithms have information on their goal state, in which it make the searching process more efficient. This information is obtained by something called a heuristic. We also learnt about the algorithms of Informed Search, which is:

• Greedy Search
• A* Tree Search
• A* Graph Search

At the end of the session the lecture give us an exercise about Informed Search‘s algorithms to make us more proficient in this topic.

Week 4

On our fourth week class, the lecturer taught us about Adversarial Search which is the search that an AI (Artificial Intelligence) used in game.

So, Adversarial Search is a search when there is an opponent changing the state of the problem every step in a direction you do not want.
Examples: Chess, business, trading, and war.

We also learnt about Minimax Algorithm, and Alpha-Beta Pruning on this week class.

Same as the previous weeks, at the end of the session the lecture give us an exercise about this week topics.