Intelligent Agents: An Introduction to Artificial Intelligence, Lecture notes of Artificial Intelligence

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INTELLIGENT AGENTS

Nguyễn Ngọc Thảo [email protected] CS420 – Artificial Intelligence

Outline

• Agents and Environments
• Good Behavior: The Concept of Rationality
• The Nature of Environments
• The Structure of Agents

What is Agent?

• AI studies how to make computers do things that people are better at if they could - Extend what they do to huge data sets - Do it fast, in near real-time - Not make mistakes
• Such systems are called Agents.

What is Agent?

• An agent perceives its environment through sensors and acts upon that environment through actuators. Agents interact with environments through sensors and actuators. What AI should fill

The agent’s behavior

• Percept: the agent’s perceptual inputs at any given instant
• Percept sequence : the complete history of everything the agent has ever perceived
• An agent’s behavior is described by the agent function that maps any given percept sequence to an action.

• Agent program: the implementation of the agent function

agent = architecture + program

mathematical practical

The Vacuum-cleaner world

• Percepts: location and contents, e.g., [A,Dirty]
• Actions: Left, Right, Suck, Do Nothing A vacuum-cleaner world with just two locations

The Vacuum-cleaner world

The agent program for a simple reflex agent in the two-state vacuum environment. function REFLEX-VACUUM-AGENT([ location,status ]) returns an action if status = Dirty then return Suck else if location = A then return Right else if location = B then return Left

Why do we need agents?

• A tool for analyze systems
• All areas of engineering can be seen as designing artifacts that interact with the world.
• AI designs artifacts that have significant computational resources and the task environment requires nontrivial decision making

Rational agents

• A rational agent is one that does the right thing.
  • Every entry in the table for the agent function is filled out correctly.
• What is “ right ” thing?
  • The actions that cause the agent to be most successful
• We need ways to measure success. Performance measure

Performance measure

• An agent, based on its percepts → generates actions sequence → environment goes to sequence of states - If this sequence of states is desirable then the agent performed well
• Performance measure evaluates any given sequence of environment states (remember, not agent states!!! ). - An objective function that determines how the agent does successfully. - 90 %? 30 %?

Rationality

• What is rational at any given time depends on

Performance measure

Define the criterion of success

Prior knowledge

What the agent knows about the environment

Percept sequence

The agent’s percept to date

Actions

What the agent can perform

Definition of a rational agent

• For example, in an exam,
  • Maximize marks based on the questions on the paper and your knowledge For each possible percept sequence, a rational agent should select an action that is expected to maximize its performance measure, given the evidence provided by the percept sequence and whatever built-in knowledge the agent has.

Omniscience, learning, and autonomy

Omniscience vs. Rationality

Omniscience Rationality

• Knows the actual outcome of its actions in advance
• No other possible outcomes
• However, impossible in real world
• Example? Maximize performance measure given the percepts sequence to date and prior knowledge Rationality is not perfection