Information-State Dialogue Modelling in Several Versions HS Dialogmanagement, SS 2002 Universität Saarbrücken Michael Götze

Overview GoDis Poesio & Traum Theory (PTT) and EDIS MIDAS SRI Autoroute Demonstrator  Question Under Discussion (QUDs)  Grounding & Obligations, Compositional DRT,...  DRT, First-order-theorem- prover  Conversational Game Theorie

What were the hopes connected to TRINDI ??? easier implementation of non-trivial dialogue theories / rapid prototyping easier portation of systems to new domains comparability of dialogue theories make theories benefit from each other (by having them implemented in one framework) etc....

Today Introduction TRINDI: the „theory-neutral“ part – the framework PTT and EDIS Conversational Game Theory (CGT) and the SRI Autoroute Demonstrator Comparison: PTT/EDIS vs. SRI Autoroute Demonstrator Conclusions?

TRINDI: the „theory-neutral“ part Information State (IS) - the state of the dialogue - its CONDITIONS can be checked can be changed with OPERATIONS Update Module updates the IS on the basis of the input Control Module Selection Module selects the next system action

Questions for implementations What does the IS look like? How does updating work? How is the next action selected? How is all this controlled?

PTT (Poesio & Traum Theory) and EDIS Agents perform Dialogue Acts (DAs) Effects of DAs update IS focus on the GROUNDING process (IS: private, grounded, not grounded) focus on social effects: OBLIGATIONS (to act) & COMMITMENTS (to propositions) (vs. intentions & beliefs) orientation towards INCREMENTAL processing (below the utterance level) exploration of accessibility conditions of pragmatic processes: REFERENCE, SCOPING (  CDRT)

IS in the PTT a new contribution results in a new discourse unit (DU) in the IS, containing obligations (OBL), the discourse history (DH), social commitments (SCP), conditions (COND) and its ID. UDUS: list of (still) ungrounded DUs GND: grounded information PDU: the previous DU CDU: the current DU INT: intentions

act: ID: 2, accept(DP, ID2) effect: accomplished via rule resolution act: ID: 2, assert(DP, PROP) effect: push(SCP, scp(DP, PROP) effect: push(COND, accept(o(DP),ID)  scp(o(DP),PROP)) act: ID: 2, ack(DP, DU1) effect: peRec(w,Gnd,w.pdu.tognd) effect: remove(DU1,UDUS) act: ID: 1, assert(DP, PROP) effect: push(COND, accept(o(DP),ID)  scp(o(DP),PROP)) ID:2, agree(DP, ID2) effect: push(SCP, scp(DP,P(ID2))) act: ID: 2, check(DP, PROP) effect: push(OBL, address(o(DP), ID) effect: push(COND, agree(o(DP),ID)  scp(DP,PROP)) ID:2, answer(DP, ID2, ID3) effect: push(SCP, ans(DP,Q(ID3), P(ID2))) act: ID: 2, direct(DP, Act) effect: push(OBL, address(o(DP), ID) effect: push(COND, accept(o(DP),ID)  obl(o(DP),Act)) act: ID: 2, info_request(DP, Q) effect: push(OBL, address(o(DP), ID))

GND:OBL:[understandingAct(W,DU3), address(C,CA2)] DH:[CA3: C2, acknowledge(C,DU2), CA2: C2, info_request(W,?helpform)] SCP: [] COND:[] UDUS:[DU3] PDU:TOGND: OBL:[address(C,CA2] DH:[CA2: C2, info_request(W,?helpform)] SCP: [] COND:[] ID:DU2 CDU:TOGND: OBL:[address(W,CA6] DH:[CA6: C2, direct(C,giveroute(W)), CA5: C2, answer(C,CA2,CA4), CA4: C2, assert(C,want(C,route))] SCP: [scp(C,want(C,route))] COND:[accept(W,CA6)  obl(W,giveroute(W))] ID:DU3 INT:[info_request(W,?start), giveroute(W), accept(W, CA6), acknowledge(W, DU3) ] W: How can I help? C: A route please.

Updating in PTT 1.Create a new DU and push it on top of UDUs. 2.Perform updates on the basis of backwards grounding acts. 3.If any other type of act is observed, record it in the dialogue history in CDU and apply the update rules for this kind of act. 4.Apply update rules to all parts of the IS which contain newly added acts.

Selection in PTT intentions lead to actions for choosing dialoge acts following factors are taken into account: –obligations –potential obligations (arising from COND) –insufficiently understood dialogue acts –intentions to perform complex acts

Controlling in PTT ????

Example (1)W: How can I help? (2)C: A route please. (3)W: Where would you like to start? (4)C: Malvern. (5)W: Great Malvern? (6)C: Yes. (7)W:Where would you like to go? (8)C: Edwinstowe. (9)W:Edwinstowe in Nottingham? (10)C:Yes. (11)W: When do you want to leave? (12)C: 6 pm. (13)W: Leaving at 6 pm? (14)C: Yes. (15)W: Do you want the quickest or the shortest route? (16)C: Quickest. (17)W: Please wait while your route is calculated.

Summary PTT...

Conversational Game Theory (CGT) Power ´79, Houghton ´86, Carletta et al. ´97 RATIONAL AGENTS plan to satisfy their GOALS by undertaking ACTIONS dialogues consist of exchanges between agents: CONVERSATIONAL GAMES, with mutually known and understood CONVERSATIONAL RULES

CGT – agents with „split personality“ Rational Agent –plans & executes conversational games (as atomic actions) Game Player –plays the conversational games

Conversational Games QW Game qw qw-r rwack cnf Ryes|Rno|Rmod INF Game infack PARDON Game unrecpdn INTERRUPT Game unimpINF game HELLO Game hello

IS in CGT Rational Agent: (plans & executes conversational games (as atomic actions)) Game Player: (plays the conversational games) PLAN:stack(actions) SCOREBOARD:set(propn) AGENDA:stack(possible_parses) CURRTOKEN:index of current token ALLTOKEN:stack(set(propn))

Updating in CGT Rational Agent: - makePlan - generates a plan - dropAction - if top goal is satisfied, remove it! - undertakeAction- if top goal is not satisfied, generate an agenda item Game Player: - 5 rules steering the network traversing

Selection in CGT Rational Agent: - only one goal in the implementation: giving a route Game Player: - 4 rules steering the selection of next moves

Controlling in CGT Control algorithm: 1.Call the update module. (dialogue monitoring) 2.Call the register-utterance module. (dialogue contribution generator) 3.Repeat Update algorithm: 1.Are there any update rules whose preconditions are fulfilled in the current IS? 2.If so, take the first one and execute the updates specified in the efects of the rule and repeat. 3.If not, stop. Register-utterance algorithm: 1.If it is the system‘s turn to say something a)call the selection module b)call the generator 2.If it is the user‘s turn to say something, call the input module.

Control Preferences: Updating & Selection Playing the game =? Parsing  What kind of parsing??? incremental & parallel parsing: –each possible parse is stored on the agenda –which is the preferred one??? confidence (confirmation moves and games win) informativity (unrestricted questions win) shorter games! (simple acknowledgments win vs. confirmations) the one the user picks out

Summary CGT Game-based theory division of labour between rational agent and the game player monitoring vs. contributing control preferences

What were the hopes connected to TRINDI ??? easier implementation of non-trivial dialogue theories / rapid prototyping easier portation of systems to new domains comparability of dialogue theories make theories benefit from each other (by having them implemented in one framework) etc....

PTT & EDISCGT ISgrounded vs. ungrounded information rational agent vs. game player UPDATE-‚dialogue act rules‘- rules on a recursive- transition- network SELECTION CONTROL-incremental below the utterance level - serial? - incremental & parallel

Conclusion? easier implementation of non-trivial dialogue theories / rapid prototyping easier portation of systems to new domains comparability of dialogue theories make theories benefit from each other (by having them implemented in one framework) ??? etc....