Agents and State Machines

Agents and State Machines

1. All AI agents go through a finite set of states. Their behavior and decision making varies from state to state. An agent transitions from one state to another due to the occurrence of an event/trigger

2. Goal based Agent

   • Goal based agents search a state space to reach a target
     • Uninformed search
       • An uninformed search does not use any clues or beforehand knowledge to speed up the search process
       • depth - first search
         • It involves searching one path to its completion before trying an alternative path
       • breadth first search
         • It will move horizontally, level by level, from left to right
     • Informed search
       • the solution is to use before hand knowledge that eliminates choices that are unlikely to lead to the goal
   • many problem solving tasks can be transformed into the problem of finding a path in a tree structure or graph
     • tree
       • A tree is a hierarchy of nodes with parent - child relationships.
     • graph
       • A graph consists of a set of nodes and a set of directed arcs between nodes