09.1 communication

7/31/2019 09.1 Communication

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Agents That CommunicateChris Bourne

Chris Christen

Bryan Hryciw



OverviewCommunication as Action

Types of Communicating Agents

A Formal Grammar for a Subset of EnglishSyntactic Analysis (Parsing)

Definite Clause Grammar (DCG)

Augmenting a Grammar

Semantic Interpretation Ambiguity and Disambiguity

A Communicating Agent

Summary



IntroductionCommunication is the intentional exchange of informationbrought about by the production and perception of signs drawnfrom a shared system of conventional signs.

Most animals employ a fixed set of signs to represent messagesthat are important to their survival: food here, predator nearby,approach, withdraw, let’s mate.

Humans, just as many other animals, use a limited number of signs to communicate (smiling, shaking hands)



IntroductionHumans are the only animal that has developed a complex,structured system of signs, known as language, that enables usto communicate most of what they know about the world.

Although other animals such as chimpanzees and dolphins haveshown vocabularies of hundreds of symbols, humans are theonly species that can communicate an unbounded number of qualitatively different messages.

Although there are other uniquely human attributes, such aswearing clothes and watching TV, Turing created his test basedon language because language is closely tied to thinking, in away these other attributes are not.



Origins & Evolution of Language

Did humans develop the use of language because weare smart, or are we smart because we use language

well?

Jerrison, 1991: Human language stems from a need for bettercognitive maps of territory. Canines rely heavily on scentmarking and their sense of smell to determine where they areand what other animals have been there. Since primates do nothave such a highly developed sense of smell, they substitutedvocal sounds for scent marking.








Semantic Interpretation

Ambiguity and Disambiguity




Communication as ActionSpeech Act:

The action available to an agent to produce language

includes talking, typing, sign language, etc.Speaker - An agent that produces a speech act

Hearer - An agent that receives a speech act

Why would agents choose to perform a speech act?

To be able to:

• Inform, Query, Answer, Request or Command, Promise, Acknowledge and Share



Communication as ActionMake the Hearer take some action:

Promise:

to do things or offer deals. Ex. I’ll shoot the wumpus if you let me share the gold.

Query:

other agents about particular aspects of the world. Ex. Have you smelled the wumpus anywhere?

Request or Command: other agents to perform actions. It can be seen as impolite tomake direct requests, so often an indirect speech act (a requestin the form of a statement or question) is used instead. Ex. I could use some help carrying this or Could you please help me carry this?



Difficulties with CommunicationSpeaking:

When is a speech act called for?

Which speech act, out of all the possibilities is the right one?

Nondeterminism

Understanding:

Given ambiguous inputs, what state of the world could havecreated these inputs?



Fundamentals of LanguageFormal Languages: Languages that are inventedand are rigidly defined. A set of strings where each

string is a sequence of symbols taken from a finiteset called the terminal symbols.

Lisp, C++, first order logic, etc.

Natural Languages: Languages that humans useto talk to one another.

Chinese, Danish, English, etc.



Component Steps of CommunicationThree steps take place in the speaker:

Intention: S want H to believe P

Generation: S chooses words W

Synthesis: S utters the words W

Four steps take place in the hearer:

Perception: H perceives W1 (ideally, W = W1)

Analysis: H infers that W1 has possible meanings P1, … , Pn Disambiguation: H infers that S intended to convey Pi (ideally,Pi = P)

Incorporation: H decides to believe Pi (or rejects it if it is outof line with what H already believes)



Models of CommunicationEncoded Message Model:

Speaker encodes a proposition into words or signs. The hearerthen tries to decode this message to retrieve the original

proposition. The meaning in the speaker’s head, the message thatgets transmitted, and the interpretation that hearer arrives at areall the same, unless there is noise during communication, or anerror in encoding or decoding occurs.

Situated Language Model:

Created because of limitations on the encoded message model.The meaning of the message depends on both the words, and thesituation.

Ex. “Diamond” refers to one thing when the subject is jewelry,and a completely different meaning when the subject is baseball.



Types of Communicating AgentsCommunicating using Tell and ask:

Agents share a common internal representation language

Agents are capable of communicating without any external

language at all

Communicating using Formal Language:

Agents make no assumptions about each other’s internal

language Agents share a communication language that is a subset of English



Tell and Ask Communication with Tell and Ask

Percepts Actions Percepts Actions

Reasoning Reasoning

KB KB

Agent A Agent B

TELL(KBB , “P”) TELL(KBA , “P”)

ASK(KBB , “Q”) TELL(KBB , “Pit (PA1) At (PA1,[2,3], SA9)”)



Formal Language

Percepts Actions Percepts ActionsReasoning Reasoning

KB KB

Agent A Agent B Language

Language





A Formal Grammar for a Subset of English Syntactic Analysis (Parsing)








Formal Grammar for a Subset of English

NP -> Pronoun

-> Noun

-> Article Noun

-> Digit Digit

-> NP PP

-> NP RelClause

RelClause -> that VP

VP -> Verb

-> VP NP

-> VP Adjective

-> VP PP

-> VP Adverb

PP -> Preposition NP

Grammar:

S -> NP VPS -> S Conjunction S



Parsing AlgorithmsThere are many algorithms for parsing

Top-down parsing

• Starting with an S and expanding accordingly

Bottom-up parsing

Combination of top-down and bottom-up

Dynamic programming techniques• Avoids inefficiencies of backtracking



Bottom-up Parse (example)

function BOTTOM-UP-PARSE(words, grammar ) returns a parse tree

forest words

loop do

if LENGTH( forest ) = 1 and CATEGORY( forest [1]) = START(grammar ) then

return forest [1]else

i choose from {1…LENGTH( forest )}

rule choose from RULES(grammar)

n LENGTH(RULE-RHS(rule))

subsequence SUBSEQUENCE( forest, i, i+n-1)

if MATCH(subsequence,RULE-RHS(rule)) then

forest[i…i+n-1] [MAKE-NODE(RULE-LHS(rule) , subsequence)]

else fail

end

forest subsequence rule

The wumpus is dead Article wumpus is dead

Article Noun is dead

NP is dead

NP Verb dead

NP Verb Adjective

NP VP Adjective

NP VP

S

Thewumpus

Article Noun

is

dead

Verb

VP Adjective

NP VP

Article the Noun wumpus

NP Article Noun

Verb is

Adjective dead

VP Verb

VP Verb Adjective

S NP VP



Definite Clause Grammer (DCG)Problems with Backus-Naur Form (BNF)

Need meaning

Context sensitive

Introduction of First Order Logic

BNF First Order Logic

S NP VP NP(s1) /\ VP(s2) S(Append(s1 ,s2))

Noun stench | … (s=“stench” \ / …) Noun(s)



DCG NotationPositive:

Easy to describe grammars

Negative:

More verbose than BNF

3 Rules:•The notation X Y Z … translate as Y(s1) /\ Z(s2)… X(Append(s1, s2,…).

•The notation X word translates as X([“word ”]).

•The notation X Y | Z | … translates as Y’(s) \ / Z’(s) \ /… X(s), where Y’

is the translation into logic of the DCG expression Y.



Extending the NotationNon-terminal symbols can be augmented

A variable can appear on RHS

An arbitrary logical test can appear on RHS

DCG First Order Logic

Digit (sem) sem { 0 sem 9 }

Number (sem) Digit (sem)

Number (sem) Number (sem1) Digit (sem2)

{sem = 10 sem1 + sem2}

(s=[sem]) Digit (sem , s)

Digit (sem , s) Number (sem , s)

Number (sem , s1) /\ Digit (sem , s2) /\

sem = 10 sem1 + sem2

Number (sem , Append (s1 , s2)



OvergenerationSimple grammar can overgenerate

Ex: “Me smells a stench.”

To fix we must understand

Cases of English

Nominative - subjective - “I” Accusative - objective - “me”



New Rules

Use of Augmentation

S NP(case)

VP

PP

Pronoun(Subjective) Pronoun(Objective)

NP(subjective) VP | … Pronoun(case) | Noun | Article Noun

VP NP(Objective) | …

Preposition NP(Objective)

I | you | he | she | …

me | you | him | her | …

Changes needed to handle subjective and objective cases

S

NPs

Npo

VPPP

Pronouns

Pronouno

NPs VP | …

Pronouns | Noun | Article Noun

Pronouno | Noun | Article Noun

VP NPo | … Preposition NPo

I | you | he | she | …

me | you | him | her | …



Verb SubcategorizationNow have slight improvement

Must create a sub-categorization listVerb Subcats Example

give [NP , PP]

[NP , NP]

give the gold in 3,3 to me

give me the gold

smell [NP]

[Adjective][PP]

smell a wumpus

smell awfulsmell like a wumpus

is [Adjective]

[PP]

[NP]

Is smelly

is in 2 2

is a pit

believe [S] Believe the smelly wumpus in 2 2 is dead



Parse TreeS

NP

VP([])

VP([NP])

VP([NP,NP]) NP NP

Pronoun Pronoun Article NounVerb([NP,NP])

You give me the gold



Semantic InterpretationSemantic Interpretation: Responsible for combiningmeanings compositionally to get a set of possible interpretations

Formal Languages

Compositional Semantics: The semantics of any phrase is afunction of its subphrases

• X + Y

We can handle an infinite grammar with a finite set of rules

Natural Languages

Appears to have a noncompositional semantics

• “The batter hit the ball”

Semantic interpretation alone cannot be certain of the right interpretation of a phrase or sentence



Semantic InterpretationSemantics as DCG Augmentation

The same idea used to specify the semantics of numbersand digits can applied to the complete language of

mathematics

Exp(sem) – > Exp(sem1) Operator (op) Exp(sem2) {sem = Apply(op, sem1 , sem2)}

Exp(sem) – > ( Exp(sem) )

Exp(sem) – > Number (sem)

Digit(sem) – > sem { 0 sem 9 }

Number (sem) – > Digit (sem)

Number (sem) – > Number (sem1) Digit (sem2) { sem = 10 × sem1 + sem2 }

Operator (sem) – > sem { sem +, – ,×,÷}}



The Semantics of E 1 Semantic structure is very different from syntactic structure.

We use an intermediate form called a quasi-logical form which uses a new construction which we will call a quantified

term. “every agent” -> [" a Agent (a)]

“Every agent smells a wumpus”

$ e (e Perceive([" a Agent (a)], [$ w Wumpus(w)], Nose) During( Now, e))



Pragmatic InterpretationThrough semantic interpretation, an agent can perceive a stringof words and use a grammar to derive a set of possiblesemantic interpretations.

Now we address the problem of completing the interpretationby adding information about the current situation

Information which is noncompositional and context-dependant



Pragmatic InterpretationIndexicals: Phrases that refer directly to the current situation

“I am in Boston today.”

Anaphora: Phrases referring to objects that have beenmentioned previously

“John was hungry. He entered a restaurant.”

“After John proposed to Marsha, they found a preacher and gotmarried. For the honeymoon, they went to Hawaii.”

Deciding which reference is the right one is a part of disambiguation.



Ambiguity and DisambiguationThe biggest problem in communicative exchange isthat most utterances are ambiguous .

Squad helps dog bite victim.

Red-hot star to wed astronomer.

Helicopter powered by human flies.

Once-sagging cloth diaper industry saved by full dumps.



AmbiguityLexical Ambiguity

a word has more than one meaning

Syntactic Ambiguity (Structural Ambiguity)more than one possible parse for the phrase

Semantic Ambiguity

follows from lexical or syntactic ambiguity

Referential Ambiguitysemantic ambiguity caused by anaphoric expressions



AmbiguityPragmatic Ambiguity

Speaker and hearer disagree on what the current situationis.

Local Ambiguity

A substring can be parsed several ways.

Vagueness

Natural languages are also vague

• “It’s hot outside.”



DisambiguationDisambiguation is a question of diagnosis.

Models of the world are used to provide possibleinterpretations of a speech act.

Models of the speaker

Models of the hearer

It is difficult to pick the right interpretation becausethere may be several right ones.



DisambiguationIn general, disambiguation requires the combinationof four models:

the world model

the mental model

the language model

the acoustic model

Natural language often uses deliberate ambiguity.

Most language understanding programs ignore thispossibility



DisambiguationContext free grammars do not provide a very usefullanguage model.

Probabilistic context-free grammars (PCFG’s)

each rewrite rule has a probability associated with it

S – > NP VP (0.9)S – > S Conjunction S (0.1)



A Communicating Agent How does this all fit in to an agent that cancommunicate?

Start with the wumpus world robot slave.

Extend the grammar to accept commands

“Go east”

“Go to 2 2”

Identify the kind (i.e, command or statement) of speech as part of the quasi-logical form.



A Communicating Agent Rules for commands and statementsS(Command (rel( Hearer )) – > VP(rel)

S(Statement (rel(obj)) – > NP(obj) VP(rel)

Rules for acknowledgementsS( Acknowledge(sem)) – > Ack (sem)

Ack (True) – > yes

Ack (True) – > OK

Ack (False) – > no



Summary Agents send signals to each other using a speech act.

All animals use some conventional signs to communicate, buthumans use language in a more sophisticated way that enables

them to communicate much moreFormal language theory and phrase structure grammars areuseful tools for dealing with some aspects of natural language

Communication involves

three steps by the speaker

• intention, generation and synthesis

four steps by the hearer

• perception, analysis, disambiguation and incorporation



SummaryThe encoded message model of communication says that aspeaker encodes a representation of a proposition intolanguage, and the hearer decodes the message to uncover the

propositionThe situated language model states that the meaning of amessage is a function of both the message and the situation inwhich it occurs.

Augmenting a grammar allows us to handle many problems

Definite Clause Grammar (DCG) is an extension of BNF that allowsfor augmentations

There are many algorithms for parsing strings.

I.e. bottom up, top down, combination, and dynamic



SummaryPragmatic interpretation takes the current situation intoaccount to determine the effect of an utterance in context

Disambiguation is the process of deciding which of thepossible interpretations is the one that the speaker intended toconvey.



The End



BibliographyNorvig, Peter and Russell, Stuart, 1995. “ Artificial Intelligence A Modern Approach ”, Prentice-Hall Inc., Upper Saddle River, NewJersey.

09.1 communication

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