The document provides an overview of artificial intelligence (AI), discussing its definition, goals, and types of intelligent agents. It covers various approaches to understanding AI, including the Turing Test, cognitive modeling, and the rational agent approach, alongside characteristics of intelligent agents such as autonomy and adaptivity. Additionally, it outlines the future possibilities for AI technology, including applications in transportation and smart cities.

1. Artificial Intelligence
1. Introduction
2. Future of Artificial Intelligence
3. Characteristics of Intelligent Agents
4. Typical Intelligent Agents
5. Agents and environments .
Dr.J.SENTHILKUMAR
Assistant Professor
Department of Computer Science and Engineering
KIT-KALAIGNARKARUNANIDHI INSTITUTE OF TECHNOLOGY
02-11-2023

2. Introduction
• Artificial Means Made or produced by humans begins, Intelligence means Knowledge
and skills
• AI is one of the newest fields in science and engineering.
• AI is the study if how to make computers do thing which at the moment people do better.
• AI is also define as the Simulation of human Intelligence processes by machines,
especially computer systems.
• Specific applications of AI include expert systems, Natural Language Processing, speech
recognition and machine vision.
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

3. • Acting humanly: The Turing Test approach:
The Turing Test, proposed by Alan Turing TURING TEST (1950), was designed to
provide a satisfactory operational definition of intelligence.
• A Turing Test is a method of inquiry in artificial intelligence AI for determining whether or not a
computer is capable of thinking like a human being.
• The computer would need to possess the following capabilities:
• Natural language processing to enable it to communicate successfully in English;
• Knowledge representation to store what it knows or hears;
• Automated reasoning to use the stored information to answer questions and to draw new
conclusions;
• Machine Learning to adapt to new circumstances and to detect and extrapolate patterns.
02-11-2023 Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI INSTITUTE OF TECH

4. Thinking humanly: The cognitive modeling approach
• If we are going to say that a given program thinks like a human, we must
have some way of determining how humans think. We need to get inside
the actual workings of human minds.
• There are three ways to do this:
• Through introspection—trying to catch our own thoughts as they go by
• Through psychological experiments—observing a person in action
• Through brain imaging—observing the brain in action
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

5. Thinking rationally: The “laws of thought” approach
• The first to attempt to codify “right thinking,” that is, irrefutable reasoning
processes.
• for example, “Socrates is a man; all men are mortal; therefore, Socrates is mortal.”
• These laws of thought were supposed to govern the operation of the mind; their
study initiated the field called logic.
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

6. Definitions of AI
• The definitions on top are concerned with thought processes and reasoning, whereas the ones on
the bottom address behavior.
• The definitions on the left measure success in terms of fidelity to human performance, whereas the
ones on the right measure against an ideal performance measure, called rationality
Systems that Think like humans Systems that think rationally
Systems that act like humans Systems that act rationally
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

7. Acting rationally: The rational agent approach
• An agent is just something that acts (agent comes from the Latin agere, to
do).
• Of course, all computer programs do something, but computer agents are
expected to do more: operate
• autonomously, perceive their environment, persist over a prolonged time
period, adapt to change, and create and pursue goals.
• A rational agent is one that acts so as to achieve the best outcome or,
when there is uncertainty, the best expected outcome.
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

8. Future of AI
• Automated Transportation
• Cyborg Technology – Making Brains to communicate with robotic
• Smart Cities
• Home Robots
• Etc.,
Advantages & Disadvantages
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

9. Discussion
• https://www.javatpoint.com/types-of-artificial-intelligence
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

10. Gate Questions and Answers
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

11. What is an Agent?
•An Agent is anything that can be viewed as –
Perceiving its environment through sensors and
acts upon the environment through actuators
•An Agent program runs in cycles of:
• Perceive
• Think
• Act
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

12. • Characteristics of Intelligent Agents
• An agent is anything that can be viewed as perceiving its environment through sensors
and acting upon that environment through actuators.
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

13. • TYPE OF AGENTS
• A human agent has eyes, ears, and other organs for sensors and
hands, legs, vocal tract, and so on for actuators.
• A robotic agent might have cameras and infrared range finders for
sensors and various motors for actuators.
• A software agent receives keystrokes, file contents, and network
packets as sensory inputs and acts on the environment by displaying on
the screen, writing files, and sending network packets
• percept to refer to the agent’s perceptual inputs at any given instant.
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

14. • How Agents Should Act
• A Rational agent is one that does the right thing.
• The right action is the one that will cause the agent to be most successful.
• The problem of deciding how and when to evaluate the success.
• The term performance measures for the how – the criteria that determine how successful
an agent is. Need not fixed measure suitable for all agents.
• The agent for subjective opinion of how happy it is with its own performance, but some
agents would be unable to answer and others would delude themselves.
• Performance measure imposed by some authority. We as outside observers establish a
standard of what it means to be successful in an environment and use it to measure the
performance of agents.
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

15. • Characteristics and Applications of Intelligent Agents:
• Situatedness – Agent Receives some form of sensory input from its environment it then
performs some actions that change its environment in some way.
• Autonomy – An Agent is able to act without direct intervention from humans or other
agents. This type of agent has almost complete control over it own actions and internal
state.
• Adaptivity – it is capable of reacting flexibly to changes within its environment. It is able
to accept goal directed initiatives when appropriate and is also capable of learning from
its own experiences, environment and interaction with others.
• Sociability – Several traits or abilities exist which many people think of when they are
discussing about intelligent agents.
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

16. • Internal Characteristics:
• Learning/Reasoning – Learn from previous experience and successively adapt its own behaviour
to the environment.
• Reactivity – Reacting or information from its environment.
• Autonomy – Control over its actions and internal states.
• Goal – Oriented – well – defined goals and gradually influence its environment and so achieve its
own goal.
• External Characteristics:
• Communications
• Cooperation
• Mobility
• Character
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

17. • There are four main aspects that needs to be taken into
consideration when designing an intelligent agent.
• Percepts – Information that the agent receives
• Actions – What the agent needs to do or can do to achieve its object.
• Goals – The factor that the agent is trying to achieve.
• Environment – the environment in which the agent will be working in.
The environment in which the agent performs is probably the most
important aspect that needs to be considered as this affects the
outcome of the percepts, actions and goals.
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

18. • Agent Function – an agents behavior is described by the agent
function that maps any given percept sequence to an action.
F: P*  A
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

19. •Task Environment:
• We must think about task environment which are essentially the
Problems to which rational agent are the solutions.
• Specifying the Task Environment:
• The Rationality of the simple vaccum-cleaner agent needs specifications
of
• Performance measure
• Environment
• Agent’s Actuators
• Sensors
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

20. • PEAS (Performance, Environment, Actuators, Sensors)
• All thèse are group together under the heading of the task environment.
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

21. • PEAS (Performance, Environment, Actuators, Sensors)
• Example
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH

22. • Properties of task environments:
• Fully observable vs Partially observable
• Deterministic vs Stochastic
• Episodic vs Sequential
• Static vs Dynamic
• Discrete vs Continuous
• Single Agent vs Multiagent
02-11-2023
Dr.J. SENTHIL KUMAR AP/CSE KIT-KALAIGNARKARUNANIDHI
INSTITUTE OF TECH