Differences in Artificial Intelligence
Difference between Intelligence and Artificial Intelligence
| Intelligence | Artificial Intelligence |
| It is a natural process or quality given to human beings. | It is programmed using human intelligence. |
| It is an actual hereditary. | It is not hereditary but a copy of human intelligence. |
| A human brain does not require any electricity to show his intelligence. | Artificial intelligence requires electricity to get an output. |
| Execution speed of a human brain is less. | Execution speed is higher than the human brain. |
| Human intelligence can handle different situations in a better way. | It is designed to handle only a few types of problems. |
| A human brain is analog. | An artificial brain is digital. |
Difference between Strong AI and Weak AI
| Strong AI | Weak AI |
| A computer machine gets capable of thinking atleast equal to human beings. | A computer machine gets a ‘thinking’ like feature to make it more powerful. |
| A machine can perform tasks on its own, just like human beings. | A machine can perform tasks but need human intervention. |
| A computer program adds an algorithm itself to act in different situations. | Here, tasks to be performed are added manually. |
| This type of AI allows machines to solve problems in an unlimited domain. | This type of AI allows machines to solve problems in a limited domain. |
| It is an independent AI which can take the decision on its own. | It is dependent on humans and can simulate like human beings. |
| Currently, strong AI does not exist in the real world. | Weak AI is in its advance phase of working. |
| There is no proper example of it. | Example: Automatic car, APPLE Siri, etc. |
Difference between Uninformed Search and Informed Search
| Uninformed Search | Informed Search |
| It is a search strategy with no additional information. It only contains the current state information. | It is a search strategy which carries some additional information with the current state information. |
| It is less efficient to use uninformed search technique. | It is more efficient search technique. |
| It may take more time to reach the goal node. | It mostly reaches the goal state in limited time. |
| May or may not give an optimal solution. | Mostly provides an optimal solution. |
| It is also known as Blind Search because it searches the goal blindly without having the prior knowledge. | It is also known as Heuristic Search as it searches the goal with the help of some prior knowledge. |
| An uninformed search requires more computation. | An informed search require less computation. |
| BFS, DFS, Uniform cost search are types of uninformed search. | Best first search, A* search are types of informed search. |
Difference between BFS and DFS
| BFS | DFS |
| It extends for Breadth-first search. | It extends for Depth-first search. |
| It searches a node breadthwise, i.e., covering each level one by one. | It searches a node depthwise, i.e., covering one path deeply. |
| It uses the queue to store data in the memory. | It uses the stack to store data in the memory. |
| BFS is a vertex-based algorithm. | DFS is an edge-based algorithm. |
| The structure of a BFS tree is wide and short. | The structure of a DFS tree is narrow and long. |
| The oldest unexpanded node is its first priority to explore it. | The nodes along the edge are explored first. |
| BFS is used to examine bipartite graph, connected path as well as shortest path present in the graph. | DFS is used to examine a two-edge connected graph, acyclic graph, and also the topological order. |
Difference between A* search and AO* search
| A* search | AO* search |
| A* search is an OR graph algorithm. | AO* search is an AND/OR graph algorithm. |
| It finds only one solution. | It finds more than one solution by combining one or more branches. |
| It follows the best-first search strategy. | It also follows the best-first search strategy. |