Stuart Russell and Peter Norvig
Where do and have they worked? What are their main interests?
How do humans think?
Cognitive Science is relatively new field that is trying to answer this question.
In the study of "intelligence", many aspects are missed if studied in isolation of human or robot bodies.
A true "artificial intelligence" must be capable of interacting with its world.
Turing Test: a computer is intelligent if a human interrogator, after posing some written questions, cannot tell whether the written responses come from a person or from a computer.
xkcd version and another one (thanks Brock Wilcox)
Rationality: doing the right thing, given what is known.
Logical reasoning systems.
Problems:
Agent: computer programs that
Rational agent: an agent that acts to achieve the best outcome, or best average outcome if the agent has incomplete knowledge
Russell and Norvig take the view of rational agents in describing data structures and algorithms.
An agent "perceives its environment through sensors and acts upon that environment through actuators."
An agent's choice of action can depend on the entire history of percepts observed previously, but not on anything it has not perceived.
But, which action to choose? A rational agent is one that does the "right thing", which depends on the performance measure.
The performance measure should be designed to reflect what one actually wants in the environment, rather than how one suspects the agent should behave. Define it in terms of effects of actions on the environment, rather than in terms of the agent's program.
Rational behavior is not perfect, because an agent cannot know everything about the environment, including past, present, and future. We focus on maximizing expected performance, given what we know about probabilities of things happening in the environment.
Specify the task environment (PEAS):
Agent Types | Performance Measure | Environment | Actuators | Sensors |
---|---|---|---|---|
medical diagnosis system | healthy patient, reduced costs | patient, hospital, staff | display of questions, tests, diagnoses, treatments, referrals | |
satellite image analysis system | correct image categorization | downlink from orbiting satellite | display of scene categorization | color pixel arrays |
part-picking robot | percentage of parts in correct bins | conveyor belt with parts; bins | jointed arm and hand | camera, joint angle sensors |
refinery controller | purity, yield, safety | refinery, operators | valves, pumps, heaters, displays | temperature, pressure, chemical sensors |
interactive English tutor | student's score on test | set of students, testing agency | display of exercies, suggestions, corrections | keyboard entry |
Task Environment | Observable | Agents | Deterministic | Episodic | Static | Discrete |
---|---|---|---|---|---|---|
crossword puzzle | fully | single | deterministic | sequential | static | discrete |
chess with clock | fully | multi | deterministic | sequential | semi | discrete |
poker | partially | multi | stochastic | sequential | static | discrete |
backgammon | fully | multi | stochastic | sequential | static | discrete |
taxi driving | partially | multi | stochastic | sequential | dynamic | continuous |
medical diagnosis | partially | single | stochastic | sequential | dynamic | continuous |
image analysis | fully | single | deterministic | episodic | semi | continuous |
part-picking robot | partially | single | stochastic | episodic | dynamic | continuous |
refinery controller | partially | single | stochastic | sequential | dynamic | continuous |
interactive English tutor | partially | multi | stochastic | sequential | dynamic | discrete |
Reflex agents
Model-based reflex agents
Goal-based agents
Utility-based agents
Using learning to modify each of the above.