Information, action and negotiation in dialogue systems

1. Information, action and negotiation in dialogue systems Staffan Larsson sl@ling.gu.se Kings College, Jan 2001

2. Overview • dialogue modelling • the information state approach & TrindiKit • GoDiS – a dialogue system • action- and information oriented dialogue • negotiative dialogue

3. Dialogue modelling • Theoretical motivations • find structure of dialogue • explain structure • relate dialogue structure to informational and intentional structure • Practical motivations • build dialogue systems to enable natural human-computer interaction • speech-to-speech translation • ...

4. Informal approaches to dialogue modelling • speech act theory (Austin, Searle, ...) • utterances are actions • illocutionary acts: ask, assert, instruct etc. • discourse analysis (Schegloff, Sacks, ...) • turn-taking, pre-sequences etc. • dialogue games (Sinclair & Coulthard,...) • structure of dialogue segments (rather than separate utterances) • can e.g. be encoded as regular expressions or finite automata • qna-game -> question qna-game* answer

5. Computational approaches implemented in systems and toolkits • finite state automata (CLSU toolkit, Nuance) • frame-based (Philips, SpeechWorks) • plan-based (TRAINS, Allen, Cohen, Grosz, Sidner, ...) • general reasoning (Sadek, ...) • information states (TRINDI: Traum, Bos, ...)

6. Inquiry- vs. action-oriented dialogue • Inquiry oriented dialogue (IOD) has the primary goal of exchanging information • regardless of whether and how this information will be used in future actions • Action oriented dialogue (AOD) has the primary goal of a participant performing or being obliged to perform an action (or plan, i.e. a complex action)

7. Inquiry-oriented dialogue • utterance types: ask, answer • Information-seeking dialogue: one DP asks the questions, the other answers them • Information-exchange (information oriented) dialogue: both DPs ask questions and provide answers • can be seen as a sequence of infoseeking dialogues, possibly with embedded subdialogues

8. Action-oriented dialogue • utterance types: request, confirm • In simple AOD, only one participant becomes obliged/comitted to some action or plan • Actions can either be performed ”online” while the dialogue is happening, or they may be stored as a plan to be performed after the dialogue (”offline”)

9. Negotiative dialogue • utterance types: suggest, accept, reject • What is it? • Negotiation is a type of problem-solving • Possible definition of negotiative dialogue: DPs discuss several alternative solutions to a problem before choosing one of them • Negotiation does not imply conflicting goals • perhaps not 100% correspondence to everyday use of the word “negotiation”, but useful to keep collaborativity as a separate dimension from negotiation • Both AOD and IOD can be negotiative • in a flight information service, the user does not become obliged to fly anywhere; so it’s IOD • but several different flights may be discussed

10. Negotiation tasks • Some factors influencing negotiation • distribution of information between DPs (who knows what) • whether DPs must commit jointly (e.g. Coconut) or one DP can make the comittment (e.g. flight booking) • We’re initially trying to model negotiation in flight booking • sample dialouge • U: flights to paris on september 13 please • S: there is one flight at 07:45 and one at 12:00 • U: what airline is the 12:00 one • S: the 12:00 flight is an SAS flight • U: I’ll take the 12:00 flight please • Sys provides alternatives, User makes the choice • Sys knows timetable, User knows when he wants to travel etc.

11. Degrees of negotiativity • non-negotiative dialogue: only one alternative is discussed • semi-negotiative dialogue: a new alternative can be introduced by altering parameters of the previous alternative, but previous alternatives are not retained • negotiative dialogue: several alternatives can be introduced, and old alternatives are retained and can be returned to

12. BDI: agents • What is needed for intelligent behaviour? • perception • Beliefs • Desires • planning and decistion making ability (deliberation) • Intentions • ability to act • To interact, also need social attitudes • common ground • obligations¨¨¨ • committments • rights

13. from AI: • actions (e.g. buy a ticket) have • preconditions ( seller has ticket, buyer has money) • decomposition ( … ) • effects

14. BDI and speech acts • ”normal” actions affect the external world • speech acts affect mental states of agents • i.e. their beliefs, desires, intentions, … • so, speech acts can be described in terms of preconditions and effects on mental states • ConvinceByInform(S, H, P) [Allen] • roles: S=speaker, H=hearer, P=proposition • precondition: bel(S, P) • effect: bel(H, P)

15. later developments • Traum • incorporate social attitudes • model the fact that utterances are not always successful • initiate_assert(S, H, P) • precondition: int( S, mbel( S, H, P ) ) • effect: bel( H, int( S, mbel( S, H, P ) ) ) • acknowledge_assert( S, H, P ) • precondition: bel( S, int( H, mbel( S, H, P ))) • effect: mbel( S, H, P )