INTENTIONS AND INFORMATION IN DISCOURSE 
Nicholas Asher 
IRIT, Universit4 Paul Sabatier, 
118 Route de Narbonne, 
31062 Toulouse, CEDEX, 
France 
asher@irit, fr 
Alex Lascarides 
Department of Linguistics, 
Stanford University, 
Stanford, 
Ca 94305-2150, 
USA, 
alex~csli, stanford, edu 
Abstract 
This paper is about the flow of inference between com- 
municative intentions, discourse structure and the do- 
main during discourse processing. We augment a the- 
ory of discourse interpretation with a theory of distinct 
mental attitudes and reasoning about them, in order to 
provide an account of how the attitudes interact with 
reasoning about discourse structure. 
INTRODUCTION 
The flow of inference between communicative intentions 
and domain information is often essential to discourse 
processing. It is well reflected in this discourse from 
Moore and Pollack (1992): 
(1)a. George Bush supports big business. 
b. He's sure to veto House Bill 1711. 
There are at least three different interpretations. Con- 
sider Context 1: in this context the interpreter I be- 
lieves that the author A wants to convince him that 
(lb) is true. For example, the context is one in which 
I has already uttered Bush won't veto any more bills. 
I reasons that A's linguistic behavior was intentional, 
and therefore that A believes that by saying (la) he 
will convince I that Bush will veto the bill. Even if I 
believed nothing about the bill, he now infers it's bad 
for big business. So we have witnessed an inference 
from premises that involve the desires and beliefs of A 
(Moore and Pollack's "intentional structure"), as well 
as his linguistic behavior, to a conclusion about domain 
information (Moore and Pollack's "informational struc- 
ture"). 
Now consider Context 2: in this context I knows that 
A wants to convince him of (la). As in Context 1, I 
may infer that the bill is bad for big business. But now, 
(lb) is used to support (la). 
Finally, consider Context 3: in this context I knows 
that House Bill 1711 is bad for big business, but doesn't 
know A's communicative desires prior to witnessing 
his linguistic behaviour. From his beliefs about tile 
domain, he infers that supporting big business would 
cause Bush to veto this bill. So, A must. have uttered 
(la) to support (lb). Hence I realises that A wan~ed 
him to believe (lb). So in contrast to Contexts 1 and 2, 
we have a flow of inference from informational structure 
to intentional structure. 
This story makes two main points. First, we agree 
with Moore and Pollack that we must represent both 
the intentional import and the informational import 
of a discourse. As they show, this is a problem for 
current formulations of Rhetorical Structure Theory 
(RST) (Thompson and Mann, 1987). Second, we go 
further than Moore and Pollack, and argue that rea- 
soning about beliefs and desires exploits different rules 
and axioms from those used to infer rhetorical relations. 
Thus, we should represent intentional structure and dis- 
course structure separately. But we postulate rhetorical 
relations that express the discourse function of the con- 
stituents in the communicative plan of the author, and 
we permit interaction between reasoning about rhetor- 
ical relations and reasoning about beliefs and desires. 
This paper provides the first steps towards a formal 
analysis of the interaction between intentional struc- 
ture and informational structure. Our framework for 
discourse structure analysis is SDRT (Asher 1993). The 
basic representational structures of that theory may be 
used to characterise cognitive states. We will extend the 
logical engine used to infer rhetorical relations--DiCE 
(Lascarides and Asher 1991, 1993a, 1993b, Lascarides 
and Oberlander 1993)--to model inferences about in- 
tentional structure and its interaction with informa- 
tional structure. 
BUSH'S REQUIREMENTS 
We must represent both the intentional import and 
the informational import of a discourse simultaneously. 
So we need a theory of discourse structure where dis- 
course relations central to intentional import and to 
informational import can hold simultaneously between 
the same constituents. A logical framework in which all 
those plausible relations between constituents that are 
consistent with each other are inferred, such as a non- 
monotonic logic like that in DICE (Lascarides and Asher, 
1993a), would achieve this. So conceivably, a similar 
nonmonotonic logic for RST might solve the problem 
of keeping track of the intentional and informational 
34 
structure simultaneously. 
But this would work only if the various discourse rela- 
tions about intentions and information could simultane- 
ously hold in a consistent knowledge base (KB). Moore 
and Pollack (1992) show via discourse (2) that the cur- 
rent commitment to the nucleus-satellite distinction in 
RST precludes this. 
(2)a. Let's go home by 5. 
b. Then we can get to the hardware store 
before it closes. 
c. That way we can finish the bookshelves tonight. 
From an intentional perspective, (2b) is a satellite to 
(2a) via Motivation. From an informational perspec- 
tive, (2a) is a satellite to (2b) via Condition. These 
two structures are incompatible. So augmenting rtsT 
with a nonmonotonic logic for inferring rhetorical rela- 
tions would not yield a representation of (2) on multiple 
levels in which both intentional and informational re- 
lations are represented. In SDRT, on the other hand, 
not all discourse relations induce subordination, and 
so there is more scope for different discourse relations 
holding simultaneously in a consistent KB. 
Grosz and Sidner's (1986) model of discourse inter- 
pretation is one where the same discourse elements are 
related simultaneously on the informational and inten- 
tional levels. But using their framework to model (1) is 
not straightforward. As Grosz and Sidner (1990) point 
out: "any model (or theory) of the communication sit- 
uation must distinguish among beliefs and intentions 
of different agents," but theirs does not. They repre- 
sent intentional structure as a stack of propositions, and 
different attitudes aren't distinguished. The informal 
analysis of (1) above demands such distinctions, how- 
ever. For example, analysing (1) under Context 3 re- 
quires a representation of the following statement: since 
A has provided a reason why (lb) is true, he must want 
I to believe that (lb) is true. It's unclear how Grosz 
and Sidner would represent this. SDRT (hsher, 1993) is 
in a good position to be integrated with a theory of cog- 
nitive states, because it uses the same basic structures 
(discourse representation structures or DRSs) that have 
been used in Discourse Representation Theory (DRT) 
to represent different attitudes like beliefs and desires 
(Kamp 1981, Asher 1986, 1987, Kamp 1991, Asher and 
Singh, 1993). 
A BRIEF INTRODUCTION TO 
SDRT AND DICE 
In SDRT (Asher, 1993), an NL text is represented by a 
segmented DRS (SDRS), which is a pair of sets contain- 
ing: the DRSS or SDRSs representing respectively sen- 
tences and text segments, and discourse relations be- 
tween them. Discourse relations, modelled after those 
proposed by Hobbs (1985), Polanyi (1985) and Thomp- 
son and Mann (1987), link together the constituents of 
an SDRS. We will mention three: Narration, Result and 
Evidence. 
• SDRSS have a hierarchical configuration, and SDRT 
predicts points of attachment in a discourse structure 
for new information. Using DICE we infer from the 
reader's knowledge resources which discourse relation 
should be used to do attachment. 
Lascarides and Asher (1991) introduce default rules 
representing the role of Gricean pragmatic maxims and 
domain knowledge in calculating the value of the up- 
date function (r, a, fl), which means "the representation 
fl of the current sentence is to be attached to a with a 
discourse relation, where a is an open node in the repre- 
sentation r of the text so far". Defaults are represented 
by a conditional--¢ > ¢ means 'if ¢, then normally ¢. 
For example, Narration says that by default Narration 
relates elements in a text. 
• Narration: (v, c~,/3) > garration(c~,/3) 
Associated axioms show how Narration affects the tem- 
poral order of the events described: Narration and the 
corresponding temporal axioms on Narration predict 
that normally the textual order of events matches their 
temporal order. 
The logic on which DICE rests is Asher and Mor- 
reau's (1991) Commonsense Entailment (CE). Two pat- 
terns of nonmonotonic inference are particularly rele- 
vant here. The first is Defeasible Modus PontEs: if one 
default rule has its antecedent verified, then the con- 
sequent is nonmonotonically inferred. The second is 
the Penguin Principle: if there are conflicting default 
rules that apply, and their antecedents are in logical 
entailment relations, then the consequent of the rule 
with the most specific antecedent is inferred. Lascarides 
and Asher (1991) use DICE to yield the discourse struc- 
tures and temporal structures for simple discourses. 
But the theory has so far ignored how A's intentional 
structure--or more accurately, I's model of A's inten- 
tional structure--influences I's inferences about the do- 
main and the discourse structure. 
ADDING INTENTIONS 
To discuss intentional structure, we develop a language 
which can express beliefs, intentions and desires. Fob 
lowing Bratman (forthcoming) and Asher and Singh 
(1993), we think of the objects of attitudes either as 
plans or as propositions. For example, the colloquial 
intention to do something--like wash the dishes--will 
be expressed as an intention toward a plan, whereas 
the intention that Sue be happy is an intention toward 
a proposition. Plans will just consist of sequences of ba- 
sic actions al; a2;... ;an. Two operators--7~ for about 
to do or doing, and 7:) for having done--will convert ac- 
tions into propositions. The attitudes we assume in our 
model are believes (BA¢ means 'A believes ¢'), wants 
(WA¢ means 'A wants ¢'), and intends (ZA¢ means 
'A intends ¢'). All of this takes place in a modal, dy- 
namic logic, where the propositional attitudes are sup- 
plied with a modal semantics. To this we add the modal 
conditional operator >, upon Which the logic of DICE is 
35 
based. 
Let's take a closer look at (1) in Context 1. Let the 
logical forms of the sentences (la) and (lb) be respec- 
tively a and/3. In Context 1, I believes that A wants 
to convince him of/3 and thinks that he doesn't believe 
already. Following the DRT analysis of attitudes, we 
assume I's cognitive state has embedded in it a model 
of A's cognitive state, which in turn has a represen- 
tation of I's cognitive state. So )'VABI/3 and BA~BI/3 
hold in I's KB. Furthermore, (v, (~,/3) A Info(c~,/3) holds 
in I's KB, where Info(a,/3) is a gloss for the seman- 
tic content of a and /~ that I knows about) I must 
now reason about what A intended by his particular 
discourse action. I is thus presented with a classical 
reasoning problem about attitudes: how to derive what 
a person believes, from a knowledge of what he wants 
and an observation of his behaviour. The classic means 
of constructing such a derivation uses the practical syl- 
logism, a form of reasoning about action familiar since 
Aristotle. It expresses the following maxim: Act so as 
to realize your goals ceteris paribus. 
The practical syllogism is a rule of defeasible reason- 
ing, expressible in CE by means of the nonmonotonic 
consequence relation ~. The consequence relation 0~¢ 
can be stated directly in the object language of CE by 
a formula which we abbreviate as ~¢, ¢) (Asher 1993). 
We use 2_(¢, ¢) to state the practical syllogism. First, 
we define the notion that the KS and ¢, but not the KB 
alone, nonmonotonically yield ¢: 
* Definition: 
¢)  I(KB A ¢, ¢) ^ I(KB, ¢) 
The Practical Syllogism says that if (a) A wants ¢ but 
believes it's not true, and (b) he knows that if g, were 
added to his KB it would by default make ¢ true even- 
tually, then by default A intends ¢. 
* The Practical Syllogism: 
(a) (WA(¢) A 
(b) BA(3Cb(¢, evenfually(¢)))) > 
(c) 
The Practical Syllogism enables.I to reason about A's 
cognitive state. In Context 1, when substituting in the 
Practical Syllogism BI/3 for ¢, and (r, c~,/3) A Info(oq j3) 
for ¢, we find that clause (a) of the antecedent to the 
Practical Syllogism is verified. The conclusion (c) is 
also verified, because I assumes that A's discourse act 
was intentional. This assumption could be expressed 
explicitly as a >-rule, but we will not do so here. 
Now, abduction (i.e., explanatory reasoning) as well 
as nonmonotonic deduction is permitted on the Prac- 
tical Syllogism. So from knowing (a) and (c), I can 
conclude the premise (b). We can state in cE an 'ab- 
ductive' rule based on the Practical Syllogism: 
* The hbductive Practical Syllogism I (APSl) 
(}/~\]A(¢) A ~A(~¢) A ~'A(¢)) > 
BA (:1¢b(¢, evenLually(¢))) 
1This doesn't necessarily include that House Bill 1711 is 
bad for big business. 
hPsl allows us to conclude (b) when (a) and (c) of 
the Practical Syllogism hold. So, the intended action 
¢ must be one that A believes will eventually make ¢ 
true. 
When we make the same substitutions for ¢ and 
!/' in APSl as before, I will infer the conclusion of 
APS1 via Defeasible Modus Ponens: BA(J.kb((r, 0~,/3) ^ 
Info(cq/3), eventually(B1~3))). That is, I infers that A 
believes that, by uttering what he did, I will come to 
believe/3. 
In general, there may be a variety of alternatives that 
we could use to substitute for ¢ and ¢ in APSl, in a 
given situation. For usually, there are choices on what 
can be abduced. The problem of choice is one that 
Hobbs e~ hi. (1990) address by a complex weighting 
mechanism. We could adopt this approach here. 
The Practical Syllogism and APS 1 differ in two impor- 
tant ways from the DICE axioms concerning discourse 
relations. First, APS1 is motivated by an abductive 
line of reasoning on a pattern of defeasible reasoning 
involving cognitive states. The DICE axioms are not. 
Secondly, both the Practical Syllogism and hPsl don't 
include the discourse update function (r, c~,/3) together 
with some information about the semantic content of a 
and/3 in the antecedent, while this is a standard feature 
of the DICE axioms for inferring discourse structure. 
These two differences distinguish reasoning about in- 
tentional structures and discourse structures. But dis- 
course structure is linked to intentional structure in the 
following way. The above reasoning with A's cognitive 
state has led I to conclusions about the discourse func- 
tion of ~. Intuitively, a was uttered to support /3, or 
a 'intentionally supports' /3. This idea of intentional 
support is defined in DICE as follows: 
* Intends to Support: 
Isupport(c~, fl) ~-* (WA(B,~3) A BA(-~13,~) A 
BA (~bh((r, ~,/3)hInfo(~,/3), even*ually( B1/3) ) ) ) 
In words, a intentionally supports \]3 if and only if A 
wants I to believe /3 and doesn't think he does so al- 
ready, and he also believes that by uttering a and /3 
together, so that I is forced to reason about how they 
should be attached with a rhetorical relation, I will 
come to believe/3. 
Isupport(a,/3) defines a relationship between a and/3 
at the discourse structural level, in terms of I's and A's 
cognitive states. With it we infer further information 
about the particular discourse relation that I should 
use to attach /3 to c~. Isupport(ot,/3) provides the link 
between reasoning about cognitive states and reasoning 
about discourse structure. 
Let us now return to the interpretation of (1) under 
Context 1. I concludes Isupport(o~,/3), because the right 
hand side of the *-*-condition in Intends to Support is 
satisfied. So I passes from a problem of reasoning about 
A's intentional structure to one of reasoning about dis- 
course structure. Now, I should check to see whether 
o" actually does lead him to believe/3. This is a check 
on the coherence of discourse; in order for an SDRS r to 
36 
be coherent, the discourse relations predicated of the 
constituents must be satisfiable. 2 Here, this amounts 
to justifying A's belief that given the discourse context 
and I's background beliefs of which A is aware, I will 
arrive at the desired conclusion--that he believes ft. So, 
I must be able to infer a particular discourse relation R 
between a and fl that has what we will call the Belief 
Property: (Bin A R(a, fl)) > /~1fl. That is, R must be 
a relation that would indeed license I's concluding fl 
from a. 
We concentrate here for illustrative purposes on 
two discourse relations with the Belief Property: 
Result(a, fl) and Evidence(a, fl); or in other words, a 
results in fl, or a is evidence for ft. 
* Relations with the Belief Property: 
(B,c~ A Evidence(a, fl)) > ~.~I~ 
(t31a ^ Result(a, fl)) > &fl 
The following axiom of Cooperation captures the 
above reasoning on I's part: if a Isupports fl, then it 
must be possible to infer from the semantic content, 
that either Result(a, fl) or Evidence(a, fl) hold: 
• Cooperation : 
(:l&.b((r, a, fl) A \[nfo(a, fl), Resull(a, fl))V 
~b((r, a, fl) A Info(a, fl), Evidence(a, fl))) 
The intentional structure of A that I has inferred has 
restricted the candidate set of discourse relations that 
I can use to attach fl to a: he must use Result or Evi- 
dence, or both. If I can't accommodate A's intentions 
by doing this, then the discourse will be incoherent. 
We'll shortly show how Cooperation contributes to the 
explanation of why (3) is incoherent. 
(3)a. George Bush is a weak-willed president. 
b. ?He's sure to veto House Bill 1711. 
FROM INTENTIONS TO 
INFORMATION: 
CONTEXTS 1 AND 2 
The axioms above allow I to use his knowledge of A's 
cognitive state, and the behaviour of A that he observes, 
to (a) infer information about A's communicative inten- 
tions, and (b) consequently to restrict the set of candi- 
date discourse relations that are permitted between the 
constituents. According to Cooperation, I must infer 
that one of the permitted discourse relations does in- 
deed hold. When clue words are lacking, the semantic 
content of the constituents must be exploited. In cer- 
tain cases, it's also necessary to infer further informa- 
tion that wasn't explicitly mentioned in the discourse, 
2Asher (1993) discusses this point in relation to Con- trast: 
the discourse marker butis used coherently only if the 
semantic content of the constituents it connects do indeed 
form a contrast: compare Mary's hair is black but her eyes 
are blue, with ?Mary's hair is black but John's hair i.~ black. 
in order to sanction the discourse relation. For exam- 
ple, in (1) in Contexts 1 and 2, I infers the bill is bad 
for big business. 
Consider again discourse (1) in Context 1. Intu- 
itively, the reason we can infer Result(a, fl) in the anal- 
ysis of (1) is because (i) a entails a generic (Bush vetoes 
bills that are bad for big business), and (ii) this generic 
makes fl true, as long as we assume that House Bill 
1711 is bad for big business. 
To define the Result Rule below that captures this 
reasoning for discourse attachment, we first define this 
generic-instance relationship: instance(e, ¢) holds just 
in case ¢ is (Vx)(A(x) > B(x)) and ¢ is A\[x/a~AB\[x/a~. 
For example, bird(tweety) Afly(tweety) (Tweety is a bird 
and Tweety flies) is an instance of Vx(bird(x) > fly(x)) 
(Birds fly). 
The Result Rule says that if (a) fl is to be attached to 
a, and a was intended to support fl, and (b) a entails a 
generic, of which fl and 6 form an instance, and (c) 6 is 
consistent with what A and I believe, 3 then normally, 
6 and Result(a, fl) are inferred. 
• The Result Rule: 
(a) ((r, a, fl) A Isupport(a, fl)A 
(b) ~b^T(a, ¢)^ ~b^~^~(fl, ¢) ^ instance(e, ¢)^ 
(c) co,sistent(KBi U ~BA U 6)) 
> (Res.tt(a, fl) ^ 6) 
The Result Rule does two things. First, it allows us to 
infer one discourse relation (Result) from those permit- 
ted by Cooperation. Second, it allows us to infer a new 
piece of information 6, in virtue of which Result(a, fl) 
is true. 
We might want further constraints on 6 than that in 
(c); we might add that 6 shouldn't violate expectations 
generated by the text. But note that the Result Rule 
doesn't choose between different tfs that verify clauses 
(b) and (c). As we've mentioned, the theory needs to 
be extended to deal with the problem of choice, and 
it may be necessary to adopt strategies for choosing 
among alternatives, which take factors other than logi- 
cal structure into account. 
We have a similar rule for inferring Evidence(fl, a) 
("fl is evidence for a"). The Evidence rule resembles 
the Result Rule, except that the textual order of the 
discourse constituents, and the direction of intentional 
support changes: 
* The Evidence Rule: 
(a) (if, a, fl) ^ Isuppo~t(fl, a)^ (b) ~,b^,(a, ¢)^ ~b^~^~(~, ~) ^ instance(e, ~)^ 
(c) consistent(Ks~ UKSA U6)) 
> (E, idence(Z, a) ^ 6) 
We have seen that clause (a) of the Result Rule is sat- 
isfied in the analysis of (1) in Context 1. Now, let 6 be 
the proposition that the House Bill 1711 is bad for big 
3Or, more accurately, ~i must be consistent with what I 
himself believes, and what he believes that A believes. In 
other words, KBA is I'$ model of A's KB. 
37 
business (written as bad(1711)). This is consistent with 
KBI U KBA, and so clause (c) is satisfied. Clause (b) 
is also satisfied, because (i) a entails Bush vetoes bills 
that are bad for big business--i.e., :l~B^r(a, ¢) holds, 
where ¢ is Vx((bill(x) A bad(z)) > veto(bush, x)); (it) 
fl ^/i is bill(1711) A veto(bush, 1711) A bad(1711); and 
so (iii) instance(¢,fl A/i) and IKB^T^~(fl, fl A 6) both 
hold. 
So, when interpreting (1) in Context 1, two rules ap- 
ply: Narration and the Result Rule. But the consequent 
of Narration already conflicts with what is known; that 
the discourse relation between a and fl must satisfy the 
Belief Property. So the consequent of the Result Rule is 
inferred: /i (i.e., House Bill 1711 is bad for big business) 
and Result(a, fl) .4 
These rules show how (1) can make the knowledge 
that the house bill is bad for big business moot.; one 
does not need to know that the house bill is bad for 
big business prior to attempting discourse attachment. 
One can infer it at the time when discourse attachment 
is attempted. 
Now suppose that we start from different premises, as 
provided by Context 2: BABIfl, BA~BI a and )/VABIa. 
That is, I thinks A believes that I believes Bush will 
veto the bill, and I also thinks that A wants to con- 
vince him that Bush supports big business. Then 
the 'intentional' line of reasoning yields different re- 
sults from the same observed behaviour--A's utter- 
ance of (1). Using APSl again, but substituting Bia 
for ¢ instead of B1fl, I concludes BA(I-kb((r,a,fl) A I fo(a, fl), eve t any(B a)).  
So Is vVo t (fl, a) holds. 
Now the antecedent to Cooperation is verified, and so 
in the monotonic component of cE, we infer that a and 
fl must be connected by a discourse relation R' such 
that (B1fl A R'(a, fl)) > Bla. As before, tiffs restricts 
the set of permitted discourse relations for attaching 
/? to a. But unlike before, the textual order of a and 
fl, and their direction of intentional support mismatch. 
The rule that applies this time is the Evidence Rule. 
Consequently, a different discourse relation is inferred, 
although the same information/i--that House Bill 1711 
is bad for big business--supports the discourse relation, 
and is also be inferred. 
In contrast, the antecedents of the Result and Evi- 
dence Rules aren't verified in (3). Assuming I knows 
about the legislative process, he knows that if George 
Bush is a weak willed president, then normally, he won't 
veto bills. Consequently, there is no /i that is consis- 
tent with his KB, and sanctions the Evidence or Resull 
relation. Since I cannot infer which of the permitted 
discourse relations holds, and so by contraposing the 
axiom Cooperation, a doesn't Isupport ft. And so I has 
failed to conclude what A intended by his discourse ac- 
tion. It can no longer be a belief that it will eventually 
4We could have a similar rule to the Result Rule for 
inferring Evidence(a, fl) in this discourse context too. 
SGiven the new KB, the antecedent of APSl would no 
longer be verified if we substituted ¢ with Blfl. 
lead to I believing fl, because otherwise Isupport(a, fl) 
would be true via the rule Intends To Support. Conse- 
quently, I cannot infer what discourse relation to use in 
attachment, yielding incoherence. 
FROM INFORMATION TO 
INTENTIONS: 
CONTEXT 3 
Consider the interpretation of (1) in Context 3: I has 
no knowledge of A's communicative intentions prior to 
witnessing his linguistic behaviour, but he does know 
that the House Bill 1711 is bad for big business. I has 
sufficient information about the semantic content of a 
and fl to infer Result(a, fl), via a rule given in Lascarides 
and Asher (1991): 
• Result 
(if, a, fl) ^ fl)) > ResetS(a, fl) 
Resull(a, fl) has the Belief Property, and I reasons that 
from believing a, he will now come to believe ft. Having 
used the information structure to infer discourse struc- 
ture, I must now come to some conclusions about A's 
cognitive state. 
Now suppose that BABIa is in I's KS. Then the 
following principle of Charity allows I to assume that A 
was aware that I would come to believe fl too, through 
doing the discourse attachment he did: 
• Charity: BI¢ > BABI¢ 
This is because I has inferred Result(a, fl), and since 
Result has the belief property, I will come to believe fl 
through believing a; so substituting fl for ¢ in Charity, 
BAI3Ifl will become part of I's KB via Defeasible Modus 
Ponens. So, the following is now part of I's KB: 
BA( \[-kb((V, a, fl) ^ Info(a, fl)), eventually(Blfl)). Fur- 
thermore, the assumption that A's discourse behaviour 
was intentional again yields the following as part of 
I's Km 7A((V, a, fl) A Info(a, fl)). So, substituting BIfl 
and (r, a, fl) A Info(a, fl) respectively for ¢ and ¢ into 
the Practical Syllogism, we find that clause (b) of the 
premises, and the conclusion are verified. Explanatory 
reasoning on the Practical Syllogism this time permits 
us to infer clause (a): A's communicative goals were to 
convince I of fl, as required. 
The inferential mechanisms going from discourse 
structure to intentional structure are much less well 
understood. One needs to be able to make some sup- 
positions about the beliefs of A before one can infer 
anything about his desires to communicate, and this 
requires a general theory of commonsense belief attri- 
bution on tile basis of beliefs that one has. 
IMPERATIVES AND 
PLAN UPDATES 
The revision of intentional structures exploits modes of 
speech other than the assertoric. For instance, consider 
another discourse from Moore and Pollack (1992): 
38 
(2)a. Let's go home by 5. 
b. Then we can get to the hardware store 
before it closes. 
c. That way we can finish the bookshelves tonight. 
Here, one exploits how the imperative mode affects 
reasoning about intentions. Sincere Ordering captures 
the intuition that ifA orders a, then normally he wants 
a to be true; and Wanting and Doing captures the in- 
tuition that if A wants a to be true, and doesn't think 
that it's impossible to bring a about, then by default 
he intends to ensure that c~ is brought about, either by 
doing it himself, or getting someone else to do it (cf. 
Cohen and Levesque, 1990a). 
* Sincere Ordering: 
> 
• Wanting and Doing: 
(~VA~ A ~BA~eventually(7~)) > ZA(~) 
These rules about A's intentional structure help us 
analyse (2). Let the logical forms of (2a-c) be respec- 
tively or, /3 and 7- Suppose that we have inferred by 
the linguistic clues that Result(o~,13) holds. That is, 
the action a (i.e., going home by 5pro), results in /3 
(i.e., the ability to go to the hardware store before it 
closes). Since (~ is an imperative, Defeasible Modus Po- 
nens on Sincere Ordering yields the inference that )/VA c~ 
is true. Now let us assume that the interpreter I be- 
lieves that the author A doesn't believe that c~'s being 
brought about is impossible. Then we may use Defea- 
sible Modus Ponens again on Wanting and Doing, to 
infer ZA(Tia). Just how the interpreter comes to the 
belief, that the author believes c~ is possible, is a com- 
plex matter. More than likely, we would have to encode 
within the extension of DiCE we have made, principles 
that are familiar from autoepistemic reasoning. We will 
postpone this exercise, however, for another time. 
Now, to connect intentions and plans with discourse 
structure, we propose a rule that takes an author's use 
of a particular discourse structure to be prima facie 
evidence that the author has a particular intention. The 
rule Plan Apprehension below, states that if ~ is a plan 
that A intends to do, or get someone else to do, and 
he states that 6 is possible as a Result of this action c~, 
then the interpreter may normally take the author A to 
imply that he intends 6 as well. 
• Plan Apprehension: 
(nesult(~, t3) A ZA(~) A/3 = can(6)) > ZA(r-(~; 6)) 
We call this rule Plan Apprehension, to make clear that 
it furnishes one way for the interpreter of a verbal mes- 
sage, to form an idea of the author's intentions, on the 
basis of that message's discourse structure. 
Plan Apprehension uses discourse structure to at- 
tribute complex plans to A. And when attaching/3 to 
~, having inferred Result(a, 13), this rule's antecedent is 
verified, and so we infer that 6--which in this case is to 
go to the hardware store before it closes--as part of A's 
plan, which he intends to bring about, either himself, 
or by getting another agent to do it. 
Now, we process 7- That way in 3' invokes an 
anaphoric reference to a complex plan. By the acces- 
sibility constraints in SDRT, its antecedent must \[a; 6\], 
because this is the only plan in the accessible discourse 
context. So 7 must be the DKS below: as a result of do- 
ing this plan, finishing the bookshelves (which we have 
labelled e) is possible: 
(7)Result(\[a; 
Now, substituting \[c~; ~\] and e for a and fl into the 
Plan Apprehension Rule, we find that the antecedent to 
this rule is verified again, and so its consequent is non- 
monotonically inferred: Za(T~(a; 6; e)). Again, I has 
used discourse structure to attribute plans to A. 
Moore and Pollack (1992) also discuss one of I's pos- 
sible responses to (2): 
(4)We don't need to go to the hardware store. 
I borrowed a saw from Jane. 
Why does I respond with (4)? I has inferred the ex- 
istence of the plan \[~r; 6; el via Plan Apprehension; so he 
takes the overall goal of A to be e (to finish the book- 
shelves this evening). Intuitively, he fills in A's plan 
with the reason why going to the hardware store is a 
subgoal: I needs a saw. So A's plan is augmented with 
another subgoal ~, where ~ is to buy a saw, as follows: 
Za(7~.\[c~;6;~;e\]). But since ~ holds, he says this and 
assumes that this means that A does not have to do c~ 
and 6 to achieve ~. To think about this formally, we 
need to not only reason about intentions but also how 
agents update their intentions or revise them when pre- 
sented with new information. Asher and Koons (1993) 
argue that the following schema captures part of the 
logic which underlies updating intentions: 
• VpdateZa(n\[al;... ; Z)(al;... ; aS) 
In other words, if you're updating your intentions to 
do actions al to ~,, and al to c U are already done, 
then the new intentions are to do otj+t to an, and you 
no longer intend to do al to aj. 
The question is now: how does this interact with dis- 
course structure? I is attempting to be helpful to A; 
he is trying to help realize A's goal. We need axioms to 
model this. Some key tools for doing this have been de- 
veloped in the past couple of decades--belief revision, 
intention and plan revision--and the long term aim 
would be to enable formM theories of discourse struc- 
ture to interact with these formal theories of attitudes 
and attitude revision. But since a clear understand- 
ing of how intentions are revised is yet to emerge, any 
speculation on the revision of intentions in a particular 
discourse context seems premature. 
39 
CONCLUSIONS AND 
FURTHER WORK 
We have argued that it is important to separate reason- 
ing about mental states from reasoning about discourse 
structure, and we have suggested how to integrate a 
formal theory of discourse attachment with common- 
sense reasoning about the discourse participants' cog- 
nitive states and actions. 
We exploited a classic principle of commonsense rea- 
soning about action, the Practical Syllogism, to model 
I's inferences about A's cognitive state during discourse 
processing. We also showed how axioms could be de- 
fined, so as to enable information to mediate between 
the domain, discourse structure and communicative in- 
tentions. 
Reasoning about intentional structure took a differ- 
ent form from reasoning about discourse attachment, 
in that explanatory reasoning or abduction was per- 
mitted for the former but not the latter (but cf. Hobbs 
et al, 1990). This, we argued, was a principled reason 
for maintaining separate representations of intentional 
structure and discourse structure, but preserving close 
links between them via axioms like Cooperation. Coop- 
eration enabled I to use A's communicative intentions 
to reason about discourse relations. 
This paper provides an analysis of only very simple 
discourses, and we realise that although we have in- 
troduced distinctions among the attitudes, which we 
have exploited during discourse processing, this is only 
a small part of the story. 
Though DICE has used domain specific information 
to infer discourse relations, the rules relate domain 
structure to discourse structure in at best an indirect 
way. Implicitly, the use of the discourse update fimction 
(v, c~, ~) in the DICE rules reflects the intuitively obvious 
fact that domain information is filtered through the cog- 
nitive state of A. To make this explicit, the discourse 
community should integrate work on speech acts and 
attitudes (Perrault 1990, Cohen and Levesque 1990a, 
1990b) with theories of discourse structure. In future 
work, we will investigate discourses where other axioms 
linking the different attitudes and discourse structure 
are important. 

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