EA C461 – Artificial Intelligence Intelligent Agents S.P.Vimal http://discovery.bits-pilani.ac.in/~vimalsp/1910AI/

To discuss… Agents Rational Agents Task Environments Vimal EA C461- Artificial Intelligence

Agent “An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators” “An agent’s choice of action at any given instant can depend on the entire percept sequence observed to date” Percept sequence  Complete history of everything the agent have ever perceived Vimal EA C461- Artificial Intelligence

Agent An agents behavior is described by agent function, mapping of any given percept sequence to an action An agent program internally implements the artificial agent’s agent function Vimal EA C461- Artificial Intelligence

A Simple Intelligent Agent Percept Sequence Action [A, Clean] Right [A, Dirty] Suck [B, Clean] Left [B, Dirty] [A, Clean], [A, Clean] [A, Clean], [A, Dirty] … [A, Clean], [A, Clean] ,[A, Clean] [A, Clean], [A, Clean] , [A, Dirty] Percepts: location and contents, e.g., [A, Dirty] Actions: Left, Right, Suck, NoOp Simple Agent Function Vimal EA C461- Artificial Intelligence

Good behavior (being Rational) agreeable to reason; reasonable; sensible: a rational plan for economic development. having or exercising reason, sound judgment, or good sense: a calm and rational negotiator. being in or characterized by full possession of one's reason; sane; lucid: The patient appeared perfectly rational. endowed with the faculty of reason: rational beings. of, pertaining to, or constituting reasoning powers: the rational faculty. proceeding or derived from reason or based on reasoning: a rational explanation. … Vimal EA C461- Artificial Intelligence

Good behavior (being Rational) A rational agent is the one that does the right thing Right action is the one that cause the agent to be more successful Appropriate performance measures for the vacuum world Amount of dirt cleaned in a duration Clean squares at ever time slots How do we say an action is rational at a given point of time? Vimal EA C461- Artificial Intelligence

Rational Agents For each possible percept sequence, a rational agent should select an action that is expected to maximize it’s performance measure ,given the evidence provided by the percept sequence and whatever the built-in knowledge, the agent has. Is our Vacuum Cleaner Agent rational? Vimal EA C461- Artificial Intelligence

Rational Agents Is an omniscient agent rational? Learning  autonomy Maximizing actual performance Vs. Maximizing expected performance Learning  autonomy A rational agent is autonomous Learn to compensate for partial / incorrect knowledge Vimal EA C461- Artificial Intelligence

Task Environment Task environments are “problems” for which the rational agents are the “solutions” Includes Performance measure Environment Actuator Sensors Vimal EA C461- Artificial Intelligence

Task Environment Agent Type Performance Measures Environment Actuators Sensors Taxi Driver Safe, Fast, Legal, Comfort, Maximize Profits Roads, other traffic, pedestrians, customers Steering, accelerators, brake, signal, horn Camera, sonar, GPS, Speedometer, keyboard, etc Medical diagnosis system Healthy patient, minimize costs, lawsuits Patient, hospital, staff Screen display (questions, tests, diagnoses, treatments, referrals) Keyboard (entry of symptoms, findings, patient's answers) PEAS Descriptions Vimal EA C461- Artificial Intelligence

Properties of Task Environment Fully Observable (vs. Partly Observable) Agent sensors give complete state of the environment at each point in time Sensors detect all the aspect that are relevant to the choice of action Deterministic (vs. Stochastic) Next state of the environment is completely determined by the current state and the action executed by the agent Strategic environment Vimal EA C461- Artificial Intelligence

Properties of Task Environment Episodic (vs. Sequential) Agent’s experience can be divided into episodes, each episode with what an agent perceive and what is the action Next episode does not depend on the previous episode Current decision will affect all future sates in sequential environment Static (vs. Dynamic) Environment doesn’t change as the agent is deliberating Semi dynamic Vimal EA C461- Artificial Intelligence

Properties of Task Environment Discrete (vs. Continuous) Depends the way time is handled in describing state, percept, actions Chess game : discrete Taxi driving : continuous Single Agent (vs. Multi Agent) Competitive, cooperative multi-agent environments Communication is a key issue in multi agent environments Vimal EA C461- Artificial Intelligence

Task Environment Chess with a clock Chess without a clock Taxi Driving Fully observable Deterministic Episodic Static Discrete Single agent Example of Task Environments and Their Classes Vimal EA C461- Artificial Intelligence

Structure of Agents Agent = Architecture + Program Implements Agent Function, performs mapping of percepts to actions Computing device Running Agent Program, with sensors & actuators Vimal EA C461- Artificial Intelligence

Vimal EA C461- Artificial Intelligence