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INTELLIGENT AGENTS. An agent is anything that can be viewed as perceiving its environment through sensors and acting upon the environment through effectors. Humans Robots Programs. Structure of an INTELLIGENT AGENTS. Vacuum-Cleaner. Rational Agent.
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An agent is anything that can be viewed as perceiving its environment through sensors and acting upon the environment through effectors Humans Robots Programs
Rational Agent A rational agent is one that does the right thing
Rationality • Rational Agent • Performance Measures • Rationality • Performance Measure that defines the criterion of success • Prior Knowledge of the Agent • Actions that can be performed by the Agent • Percept Sequence of the Agent up to date
Rational Agent 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.
Environments • The first step in designing an Agent • Task Environment • Performance Environment Actuators Sensors description • Automated Taxi Driver • P : safe, fast, legal, comfort, maximize profit • E : roads, other vehicles-traffics, pedestrians, customers • A : steering, accelerator, brake, signal, clutch, horn, display, lights • S : cameras, sonar, speedometer, GPS, odometer, engine sensors, keyboard
Other PEAS… • Medical Diagnosis System • Satellite Image Analysis System • Part-picking Robot • Refinery Controller • Interactive English Tutor
Properties of the Task Environment • Fully vs. Partially Observable • Deterministic vs. Stochastic • Episodic vs. Sequential • Static vs. Dynamic • Discrete vs. Continuous • Single Agent vs. Multi Agent
Structure of an Agent • Simple Reflex Agents • Model based Agents • Goal based Agents • Utility based Agents • Learning Agents
Summary • Agents interact with environments through actuators and sensors • The agent function describes what the agent does in all circumstances. • The performance measure evaluates the environment sequence. • A perfectly rational agent maximizes expected performance. • Agent programs implement (some) agent functions.
Summary • PEAS descriptions define task environments. • Environments are categorized along several dimensions: • Observable? Deterministic? Episodic? Static? Discrete? Single-agent? • Several basic agent architectures exist: • Reflex, reflex with state, goal-based, utility-based