Logical Agents.

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Presentation transcript:

Logical Agents

Where are we at? Finished up Search Techniques Exam next Monday HW3 (MiniMax) assigned (due NEXT Friday) Today we begin a different style of agent

Let’s play a game of Wumpus

A Typical Wumpus World

Wumpus World Description

Let’s Play Wumpus! You are in Cell (1,1) facing “North” None of the sensors register anything. Find the gold….

Exploring the Wumpus World

Exploring the Wumpus World

Exploring the Wumpus World

Exploring the Wumpus World

Exploring the Wumpus World

Exploring the Wumpus World

Exploring the Wumpus World

Exploring the Wumpus World

Motivating KB Agents Reflex agents keep the world clean, in large part, by dumb luck Searching algorithm can find the shortest path from Arad to Bucharest, but can’t easily adjust when the road from Rimnicu Vilcea to Pitesti is closed for maintenance. Logic (Knowledge-Based) agents combine general knowledge with current percepts to infer hidden aspects of current state prior to selecting actions

Knowledge Bases

Knowledge Base A generic KB agent (Fig 7.1) A knowledge base (KB) is a set of representations (sentences) of facts about the world. TELL and ASK - two basic operations to add new knowledge to the KB to query what is known to the KB Infer - what should follow after the KB has been TELLed. A generic KB agent (Fig 7.1)

Generic KB-Based Agent

Simple Knowledge-Based Agent

Representing Knowledge Problems: PAGE Formulation Percepts What can agent observe? What can sensors tell it? Actions What actuators does agent have? In what context are they applicable? Goals What are agents goals? Preferences (utilities)? How does agent evaluate them (check environment, deliberate, etc.)? Environment What are “rules of the world”? How can these be represented, simulated?

Wumpus World PAGE Description

Wumpus World: PEAS Description

Tight spots (0.86 vs. 0.31)

Tight spots (0.86 vs. 0.31)

Tight spots (0.86 vs. 0.31)

Tight spots (0.86 vs. 0.31)

Logic When we have too many states, we want a convenient way of dealing with sets of states. The sentence “It’s sunny” stands for all the states of the world in which it is sunny. Logic provides a way of manipulating big collections of sets by manipulating short descriptions instead. Instead of thinking about all the ways a world could be, we’re going to work in a language of expressions that describe those sets.

What is a logic? A formal language Syntax – what expressions are legal Semantics – what legal expressions mean Proof system – a way of manipulating syntactic expressions to get other syntactic expressions (which will tell us something new) Why proofs? Two kinds of inferences an agent might want to make: Multiple percepts  conclusions about the world Current state & operator  properties of next state

Logic in general