Rio's musings

Uninformed search functions

This we studied more aspects of intelligent systems. in particular we studied the nuances about uninformed search. There are aspects to search that determine how we search for results. the 6 Attributed are.

• States
• Any state
• Actions
• Transition Model
• Goal test
• Path cost

State graph consists of vertices and edges

Each node has a State, Parent node ,action, path cost, depth. evaluation of search strategies are also studied in this lecture.

Lastly we studied multiple uninformed search strategies.

BFS, DFS,FLS, UCS and IDS

further information inside the notes.

The first topic was that about the introduction of AI, its definitions and slight part of it’s history. It was surprising to me that it was coined more than 60 years ago. we went further in depth regarding this introduction. this included the 4 components of the AI field which includes thinking rationally, thinking humanly, acting rationally and action humanly. also learned a it on how the turing test defines it. we also learned it’s foundations(pillars) such as philosophy, etc as well as the implementations today. last part of this introduction is the application domains.

The second topic was that about the Intelligent agent design and its definitions. which perceives its environments and acts rationally. We learned how to measure the environmental factors. as well as the agent types which included reflex and utility based agents among others. lastly we needed to create a group and discuss what we needed to do for the project.