Chapter2 Intelligent Agents 20070308 chap2 1 What Is An Agent - PDF document

Chapter2 Intelligent Agents 20070308 chap2 1 What Is An Agent ? 2 20070308 chap2 1

What Is An Agent ? (cont.-1) An agent interacts with its environments through sensors and actuators. • Perceiving through sensors - human agent: eyes, ears, etc. - robot agent: cameras, infrared, etc. - software agent: receiving keystrokes, file contents, network packets, etc. • Acting through actuators - human agent: hands, legs, mouth, etc. - robot agent: arms, motors, etc. - software agent: displaying on the screen, sending network packets, etc. 3 20070308 chap2 What Is An Agent ? (cont.-2) • Agent function (abstract mathematical description) that maps any given percept sequence to an action. • Agent program (concrete implementation) that implements the agent function, running on the physical architecture to produce f . • A rational agent is one that does the right thing. 4 20070308 chap2 2

Vacuum-cleaner world Percepts: location and contents, e.g., [ A, Dirty ] Actions: Left, Right, Suck, NoOp 5 20070308 chap2 Vacuum-cleaner world (cont.) • agent function • agent program What is the right function? Can it be implemented in a small agent program? 6 20070308 chap2 3

Performance Measure The right action is the one that will cause the agent to be most successful . • The measure should be objective. • How does one evaluate success? • When does one evaluate success? • Example: to vacuum a dirty floor the cleanness of the floor the amount of dirt cleaned up the amount of electricity consumed the amount of noise generated total time and effort spent performance over a short/long time 7 20070308 chap2 Rational Agents What is rational depends on • Performance measure - degree of success • Percept sequence to date • The agent's knowledge about the environment • Actions that can be performed by the agent Definition of a rational agent For each possible percept sequence, 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. 8 20070308 chap2 4

Rational Agents (cont.) • rationality ≠ omniscience ( 全知 ) e.g. crossing the road and be flattened • rationality ≠ perfection Rationality maximizes expected performance, while perfection maximizes actual performance . • rationality = exploration + learning + autonomy e.g. lowly dung beetles, female sphex wasp Information gathering/exploration -- To maximize future rewards Learn from percepts -- To extend prior knowledge Agent autonomy -- To compensate for incorrect/partial prior knowledge 9 20070308 chap2 Specifying the Task Environment PEAS (Performance, Environment, Actuators, Sensors) e.g. Automated Taxi 10 20070308 chap2 5

Specifying the Task Environment (cont.) e.g. Medical diagnosis system Performance measure?? Healthy patients, minimize costs Environment?? Patient, hospital, staff Actuators?? Display questions, tests, treatments, diagnoses, referrals Sensors?? Keyboard entry of symptoms, findings, patient’s answer 11 20070308 chap2 Properties of Task Environments Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? Deterministic?? Episodic?? Static?? Discrete?? Single-agent?? 12 20070308 chap2 6

Properties of Task Environments ( cont.-1 ) Fully vs. partially observable : an environment is full observable when the sensors can detect all aspects that are relevant to the choice of action. Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? Deterministic?? Episodic?? Static?? Discrete?? Single-agent?? 13 20070308 chap2 Properties of Task Environments ( cont.-2 ) Fully vs. partially observable : an environment is full observable when the sensors can detect all aspects that are relevant to the choice of action. Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? Episodic?? Static?? Discrete?? Single-agent?? 14 20070308 chap2 7

Properties of Task Environments ( cont.-3 ) Deterministic vs. stochastic : if the next environment state is completely determined by the current state the executed action then the environment is deterministic. If it is deterministic except for actions of other agents, we say the environment is strategic. Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? Episodic?? Static?? Discrete?? Single-agent?? 15 20070308 chap2 Properties of Task Environments ( cont.-4 ) Deterministic vs. stochastic : if the next environment state is completely determined by the current state the executed action then the environment is deterministic. If it is deterministic except for actions of other agents, we say the environment is strategic. Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? YES NO YES NO Episodic?? Static?? Discrete?? Single-agent?? 16 20070308 chap2 8

Properties of Task Environments ( cont.-5 ) Episodic vs. sequential : In an episodic environment the agent ’ s experience can be divided into atomic steps where the agents perceives and then performs a single action. The choice of action depends only on the episode itself . Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? YES NO YES NO Episodic?? Static?? Discrete?? Single-agent?? 17 20070308 chap2 Properties of Task Environments ( cont.-6 ) Episodic vs. sequential : In an episodic environment the agent ’ s experience can be divided into atomic steps where the agents perceives and then performs a single action. The choice of action depends only on the episode itself . Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? YES NO YES NO Episodic?? NO NO NO NO Static?? Discrete?? Single-agent?? 18 20070308 chap2 9

Properties of Task Environments ( cont.-7 ) Static vs. dynamic : If the environment can change while the agent is choosing an action, the environment is dynamic. Semi-dynamic if the agent ’ s performance changes even when the environment remains the same. Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? YES NO YES NO Episodic?? NO NO NO NO Static?? Discrete?? Single-agent?? 19 20070308 chap2 Properties of Task Environments ( cont.-8 ) Static vs. dynamic : If the environment can change while the agent is choosing an action, the environment is dynamic. Semi-dynamic if the agent ’ s performance changes even when the environment remains the same. Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? YES NO YES NO Episodic?? NO NO NO NO Static?? YES YES SEMI NO Discrete?? Single-agent?? 20 20070308 chap2 10

Properties of Task Environments ( cont.-9 ) Discrete vs. continuous : This distinction can be applied to the state of the environment, the way time is handled and to the percepts/actions of the agent. Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? YES NO YES NO Episodic?? NO NO NO NO Static?? YES YES SEMI NO Discrete?? Single-agent?? 21 20070308 chap2 Properties of Task Environments ( cont.-10 ) Discrete vs. continuous : This distinction can be applied to the state of the environment, the way time is handled and to the percepts/actions of the agent. Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? YES NO YES NO Episodic?? NO NO NO NO Static?? YES YES SEMI NO Discrete?? YES YES YES NO Single-agent?? 22 20070308 chap2 11

Properties of Task Environments ( cont.-11 ) Single vs. multi-agent: Does the environment contain other agents who are also maximizing some performance measure that depends on the current agent ’ s actions? Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? YES NO YES NO Episodic?? NO NO NO NO Static?? YES YES SEMI NO Discrete?? YES YES YES NO Single-agent?? 23 20070308 chap2 Properties of Task Environments ( cont.-12 ) Single vs. multi-agent: Does the environment contain other agents who are also maximizing some performance measure that depends on the current agent ’ s actions? Solitaire Backgammom Internet Taxi shopping ( 西洋雙陸棋戲 ) ( 接龍 ) Observable?? FULL FULL PARTIAL PARTIAL Deterministic?? YES NO YES NO Episodic?? NO NO NO NO Static?? YES YES SEMI NO Discrete?? YES YES YES NO Single-agent?? YES NO NO NO 24 20070308 chap2 12