Artificial intelligence is also called machine intelligence. Human associate with the human mind such as learning and problem solving. It is used to solve various kinds of computational problems. Artificial intelligence includes programming computers for certain trait such as:
- Problem solving
- 1 Perception
- 2 Reasoning
- 2.1 Deductive reasoning
- 2.2 Inductive reasoning
- 2.3 Abductive reasoning
- 2.4 Analogical reasoning
- 2.5 Common-sense reasoning
- 2.6 Non-monotonic reasoning
- 2.7 Single state problem
- 2.8 Multi state problem
- 2.9 Problem solving agents
- 2.10 Rational agents
- 2.11 Problem solving agent
- 2.12 Component of problem solving
- 2.13 Problem statement
- 2.14 Problem solution
- 2.15 Solution space
- 2.16 Traveling in the solution space
- 2.17 Narrow
- 2.18 General
- 2.19 Strong
- 2.20 Reactive Machines
- 2.21 Limited memory
- 2.22 Theory of Mind
A percept is the input that an intelligent agent perceives at any given moment. A perception presumes sensation, where the various type of sensor who converts the simple signals into data of the system.
Reasoning is the process of deriving logical conclusion from the given facts. Such types of reasoning are:
- Deducted reasoning
- Inductive reasoning
- Abductive reasoning
- Analogical reasoning
- Common sense reasoning
- Non-monotonic reasoning
In deductive reasoning the premises is true the conclusion must also be true. E.g.
All man are mortal. Socrates is a man
_We can deduce: Socrates is mortal.
Premises support the conclusion but do not guarantee that it will be true.E.G.
Observation: All the crows that I have seen in my life is black
Conclusion: All crows are black
In this reasoning the conclusion might be wrong e.g.
- Implication: it is carries umbrella if it is raining
- Axiom: she is carrying an umbrella
- Conclusion: it is raining
Analogical reasoning works between two situations, looking for similarities and differences. E.g.
The way to obtain common sense is by learning it or experiences it. E.g. robots
Non-monotonic reasoning is used when the facts of the case are likely to change after some time. E.g.
Rule: if the wind blows
Then: the curtains swing
Collection of information that the agent decides what to do. There are two types of problems.
- Single state problem
- Multi state problem
Single state problem
When the environment is completely accessible and the agent can calculate its state after any sequence of action.
Multi state problem
When the environment is not fully accessible, the goal state may not be reachable in one action.
Problem solving agents
- Rational agents
- Problem solving agent
The agents are supposed to maximize their performance measure.
Problem solving agent
The agents which can adopt a goal.
Component of problem solving
- Problem statement
- Problem solution
- Solution space
- Traveling in the solution space
This is very essential component where we give us a feel what exactly to do.it also contain the problem information and constraint over the problem.
Mouse has to get the cheese in an hour.
It should be known that what should be the ultimate aim of the problem.
The set of the start state and all the intermediate state constitutes something is called a solution space.
Mouse has gone to various paths to go to the cheese.
Traveling in the solution space
The traveling inside the solution space requires something called operator. In case of the mouse example turn left, turn right, go straight are the operators which help us the problem inside the solution space.
There are a number of different forms of learning applied in artificial intelligence. The simplest is learning by trials and error.
The language use in artificial intelligence is:
It is a type of AI it is very able to perform a task with intelligence .It is trained only one specific task. For example Apple saris.
It can make such system which could be smarter and think like a human. System is still under research and it will take a lot of time and effort to develop such system.
In this system machine could surpass human intelligence. It can perform any task better than human with cognitive properties.
- Reactive Machine
- Limited Memory
- Theory of mind
It does not have past memory or cannot use past information. Its only performs future action and store future information. This machine is only focus on current scenarios or current situation.
Its only use the past memory or can use the past information .The data can’t be store for a long time in this memory .Self-driving cars are one of the best example of limited memory. They observe other cars speed limit and direction and nearby distance.
Theory of Mind
Theory of mind understands the human emotions and also be able to interact with human socially. This kind of machines is still not developed but researchers can do more effort to make this kind of machine.
Self-Awareness is the future of artificial intelligence.
- It’s solving the new problems.
- Its handle the information properly.
- Improved interfaces.
- Faster decisions.
- Less errors
- Intelligent agent
- Neural nets
- Expert system
Machine learning is a simple concept machine . It’s a self-learning creating algorithm. It does also allow learning new things from data. Its lead knowledge.
AI performs does smart work. Its decision making .AI leads intelligence.
Deep learning is working on the human brain that process data and creates new patterns that used in decision making.
Artificial Intelligence is a mimic human behavior.
The future is really unknown. The researchers seem disagree on a lot of the same issue. With the rate at which technology is improving it is logical to believe AI will continue to get more and more sophisticated. AI permeates many job sectors in the future. It can create new career path in many fields in future.