Week 1: Agents & Search Flashcards
What is AI? What is an agent? How about multiple agents? How does AI find solutions?
What is a rational agent?
A rational agent is an entity that
* perceives its environment and
* acts according to some rules
* to achieve its goals
Rationality
A rational agent chooses whichever action maximises the expected value of the performance measure given the percept
sequence to date
Designing rational agents:
PEAS
To design a rational agent, we must specify the task environment
What is/are
* Performance measure
* Environment(s)
* Actuators
* Sensors
Types of Environments
the environment type largely determines the agent design:
* Is the environment
* observable?
* deterministic?
* episodic?
* static?
* discrete?
* single-agent?
Programming agents
Four basic types in order of increasing generality:
* simple reflex agents
* reflex agents with state
* goal-based agents
* utility-based agents
How does the inside of the agent work
agent = architecture + program
- All agents have the same skeleton:
- Input = current percepts
- Output = action
- Program= manipulates input to produce output
Simple reflex agents
Select action on the basis of only the current percept
Large reduction in possible percept/action situations
Implemented through condition-action rules
Reflex agents with state
(model-based reflex agent)
To tackle partially observable environments
Over time, update state using world knowledge
Goal-based agents
The agent needs a goal to know which situations are desirable
- Things become difficult when long sequences of actions are required to find the goal
Typically investigated in search and planning research
Utility-based agents
Certain goals can be reached in different ways.
* Some are better, have a higher utility
Learning agents
All previous agent-programs describe methods for selecting
actions.
* They do not explain the origin of these programs.
* Learning mechanisms can be used to perform this task.
* Teach them instead of instructing them
