1. Introduction to the TrindiKit ESSLLI, Helsinki 20th Aug 2001 Staffan Larsson sl@ling.gu.se

2. What is TrindiKit? a toolkit for – building and experimenting with dialogue move engines and systems, – based on the information state approach not a dialogue system!

3. short demo architecture & concepts what’s in TrindiKit? building a system This lecture

4. Short demo web-based demo + simple GUI information state view –record –dialogue –update rules module view –active modules highlighted –asynchronous processing

5. Architecture & concepts

6. module 1 module … Total Information State (TIS) Information state proper (IS) Module Interface Variables Resource Interface Variables resource 1 control module i module j module … module n resource … resource m DME

7. an abstract data structure (record, DRS, set, stack etc.) accessed by modules using conditions and operations the Total Information State (TIS) includes –Information State proper (IS) –Module Interface variables –Resource Interface variables Information State (IS)

8. module or group of modules responsible for –updating the IS based on observed moves –selecting moves to be performed dialogue moves are associated with IS updates using IS update rules –there are also update rules no directly associated with any move (e.g. for reasoning and planning) update rules: rules for updating the TIS –rule name and class –preconditon list: conditions on TIS –effect list: operations on TIS update rules are coordinated by update algorithms Dialogue Move Engine (DME)

9. Modules (dialogue move engine, input, interpretation, generation, output etc.) –access the information state –no direct communication between modules only via module interface variables in TIS modules don’t have to know anything about other modules increases modularity, reusability, reconfigurability –may interact with user or external processes Resources (device interface, lexicons, domain knowledge etc.) –hooked up to the information state (TIS) –accessed by modules –defined as object of some type (e.g. ”lexicon”) Modules and resources

10. What’s in TrindiKit?

11. What does TrindiKit provide? High-level formalism and interpreter for implementing dialogue systems –promotes transparency, reusability, plug- and-play, etc. –allows implementation and comparison of dialogue theories –hides low-level software engineering issues GUI, WWW-demo Ready-made modules and resources –speech –interfaces to databases, devices, etc. –reasoning, planning

12. a library of datatype definitions (records, DRSs, sets, stacks etc.) –user extendible a language for writing information state update rules GUI: methods and tools for visualising the information state debugging facilities –typechecking –logs of communication modules-TIS –etc. TrindiKit contents (1)

13. A language for defining update algorithms used by TrindiKit modules to coordinate update rule application A language for defining basic control structure, to coordinate modules A library of basic ready-made modules for input/output, interpretation, generation etc.; A library of ready-made resources and resource interfaces, e.g. to hook up databases, domain knowledge, devices etc. TrindiKit contents (2)

14. Special modules and resources included with TrindiKit OAA interface resource –enables interaction with existing software and languages other than Prolog Speech recognition and synthesis modules –TrindiKit shells for off-the-shelf recognisers –currently only ViaVoice, but more on the way Possible future modules: –planning and reasoning modules –multimodal input and output

15. Asynchronous TrindiKit Internal communication uses either –OAA (Open Agent Architecture) from SRI, or –AE (Agent Environment), a stripped-down version of OAA, implemented for TrindiKit enables asynchronous dialogue management –e.g.: system can listen and interpret, plan the dialogue, and talk at the same time

16. How to build a system

17. TRINDIKIT dialogue theory (IS, rules, moves etc) domain knowledge (resources) domain-specific system Relation TrindiKit – dialogue system domain-independent DME software engineering (basic types, control flow)

18. Come up with a nice theory of dialogue Formalise the theory, i.e. decide on –Type of information state (DRS, record, set of propositions, frame,...) –A set of dialogue moves –Information state update rules, including rules for integrating and selecting moves –DME Module algorithm(s) and basic control algorithm –any extra datatypes (e.g. for semantics: proposition, question, etc.) Building a domain-independent Dialogue Move Engine

19. Domain independence of the Dialogue Move Engine The DME is domain independent, given a certain type of dialogue –information-seeking –instructional –negotiative –... Domain independence of DME is not enforced by TrindiKit, but is good practice –promotes reuse of components –forces abstraction from domain-specific details, resulting in a more general theory of dialogue

20. Specifying Infostate type the Total Information State contains a number of Information State Variables –IS, the Information State ”proper” –Interface Variables used for communication between modules –Resource Variables used for hooking up resources to the TIS, thus making them accessible from to modules use prespecified or new datatypes

21. sample infostate type declaration infostate_variable_of_type( is, IS ) :- IS = record( [ private : Private, shared : Shared ] ), Shared = record( [ com : set( proposition ), qud : stack( question ), lm : set( move ) ] ), Private = record( [ agenda: stack( action ), plan : stackset( action ), bel : set( proposition ), tmp : Shared ] ) ] ).

22. resulting infostate type PRIVATE : PLAN : stackset( Action ) AGENDA : stack( Action ) SHARED : BEL : set( Prop ) TMP : (same type as SHARED) COM : set( Prop ) QUD : stack( Question ) LM: set( Move )

23. Sample interface variable type declarations interface_variable_of_type( input, string ). interface_variable_of_type( output, string ). interface_variable_of_type( latest_speaker, speaker ). interface_variable_of_type( latest_moves, set(move) ). interface_variable_of_type( next_moves, set(move) ).

24. Specifying a set of moves amounts to specifying objects of type move (a reserved type) –there may be type constraints on the arguments of moves preconditions and effects of moves –formalised in update rules, not in the move definition itself –a move may have different effects on the IS depending e.g. on who performed it

25. sample move specifications % Social of_type( quit, move ). of_type( greet, move ). of_type( thank, move ). % Q&A of_type( ask(Q), move ) <- of_type( Q, question ). of_type(inform(P), move ) <- of_type( P, proposition). of_type( answer(R), move ) <- of_type( R, proposition) or of_type( R, ellipsis ).

26. Writing rules rule = conditions + operations –if the rule is applied to the IS and its conditions are true, the operations will be applied to the IS –conditions may bind variables with scope over the rule (prolog variables, with unification and backtracking)

27. A sample rule rule( integrateUsrAnswer, [ $/shared/lu/speaker = usr, assoc( $/shared/lu/moves, answer(R), false ), fst( $/shared/qud, Q ), $domain : relevant_answer( Q, R ), $domain : reduce(Q, R, P) ], [ set_assoc( /shared/lu/moves, answer(R),true), pop( /shared/qud ), add( /shared/com, P ) ] ).

28. A sample rule (old syntax) rule( integrateUsrAnswer, [ –val#rec( shared^lu^speaker, usr ), –assoc#rec( shared^lu^moves, answer( R ), false ), –fst#rec( shared^qud, Q ), –domain :: relevant_answer( Q, R ), –domain :: reduce(Q, R, P) –], [ –set_assoc#rec( shared^lu^moves, answer(R),true), –pop#rec( shared^qud ), –add#rec( shared^com, P ) ] ).

29. Writing rules available conditions and operations depend on the infostate type –the infostate is declared to be of a certain (usually complex) type datatype definitions provide –relations: Rel(Arg1, …, ArgN) –functions: Fun(Arg1, …, ArgN,Result) –operations: Op(ObjIn,Arg1, …, ArgN,ObjOut) New datatypes may be added

30. Writing rules: locations in TIS objects may be specified by giving a path to a location in the infostate; –paths are specified using selectors, which are similar to functions $Fun2($Fun1) ~ $Sel1/Sel2 $fst($/shared/qud) ~ $/shared/qud/fst –”$” evaluates a path and gives the object at the location specified example: –is/shared/com is a path, pointing to a location in the TIS –$is/shared/com is the object in that location –the is can be left out, giving $/shared/com

31. Writing rules: conditions (1) conditions do not change the information state if a condition fails, backtracking ensues condition syntax (incomplete) –Rel(Arg1, …, ArgN), e.g. fst($/shared/qud,Q) –Arg1:Rel(Arg2,…,ArgN), e.g. $/shared/qud:fst(Q) $domain:relevant_answer(Q,A) –Arg1 = Arg2 Q = $fst($/shared/qud) –Cond1 and Cond2 –Cond1 or Cond2 –not Cond1 –forall(Cond1, Cond2) –(Arg is object or prolog variable)

32. Writing rules: conditions (2) quantification, binding and backtracking –if an instantiation a of a variable V in a condition C is found that makes condition C true, V is bound to a –backtracking occurs until a successful instantiation of all variables in the list of conditions has been found example list of conditions fst($/shared/qud,Q), in($/shared/com,P), $domain:relevant_answer(P,Q) Explicit quantification  Q.  P. fst($/shared/qud,Q) & in($/shared/com,P) & $domain:relevant_answer(P,Q)

33. Writing rules: operations operations change the information state if an operation fails, an error is reported variable bindings survive from conditions to operations operation syntax (incomplete) –Op(Path,Arg1,…,ArgN) push(/shared/qud, Q) –Path : Op(Arg1, …,ArgN) /shared/qud : push(Q) –Store := Fun(Obj,Arg1,…,ArgN) /private/tmp/qud := push($/shared/qud,Q)

34. Specifying update algorithms uses rule classes constructs include –Rule –RuleClass –if Cond then S else T –repeat R until C –repeat R –try R –R orelse S –test C –SubAlgorithm

35. Sample update algorithm grounding, if $latest_speaker == sys then try integrate, try database, repeat downdate_agenda, store else repeat integrate orelse accommodate orelse find_plan orelse if (empty#rec( private^agenda ) then manage_plan else downdate_agenda repeat downdate_agenda if empty($/private/agenda)) then repeat manage_plan repeat refill_agenda repeat store_nim try downdate_qud

36. Specifying serial control algorithms serial constructs include –Module{:Algorithm} –if Cond then S else T –repeat R until C –repeat R –try R –R orelse S –test C –SubAlgorithm

37. Specifying concurrent control algorithms Agent 1 | Agent 2 | … | Agent N where Agent i is AgentName : { –import Module 1, – … –import Module p, –Trigger 1 => SerialAlgoritm 1, –… –Trigger m => SerialAlgoritm m } triggers: –condition(C) (C is a subset of the full condition set) –init –new_data(Stream)

38. Sample control algorithm (1) repeat ( [ select, generate, output, update, test( $program_state == run ), input, interpret, update ] )

39. Sample control algorithm (2) input: { init => input:display_prompt, new_data(user_input) => input } | interpretation: { import interpret, condition(is_set(input)) => [ interpret, print_state ] } | dme: { import update, import select, init => [ select ], condition(not empty(latest_moves)) => [ update, if val(latest_speaker,usr) then select else [] ] } | generation: { condition(is_set(next_moves)) => generate } | output: { condition(is_set(output)) => output } )).

40. From DME to dialogue system Build or select from existing components: Modules, e.g. –input –interpretation –generation –output Still domain independent the choice of modules determines e.g. the format of the grammar and lexicon

41. Domain-specific system Build or select from existing components: Resources, e.g. –domain (device/database) interface –dialog-related domain knowledge, e.g. plan libraries etc. –grammars, lexicons

42. Building resources Resource –the resource itself; exports a set of predicates Resource interface –defines the resource as a datatype T, i.e. in terms of relations, functions and operations Resource interface variable –a TIS variable whose value is an object of the type T By changing the value of the variable, resources can be switched dynamically –change laguage –change domain

43. sample resource variable type declarations (incl. resource interface) resource_type( lexiconT ). resource_variable_of_type( lexicon, lexiconT ). of_type( lexicon_travel_english, lexiconT ). of_type( lexicon_autoroute_english, lexiconT ). of_type( lexicon_travel_svenska, lexiconT ). of_type( lexicon_cellphone_svenska, lexiconT ). resource_condition(lexiconT,input_form(Phrase,Move),Lexicon) :- Lexicon : input_form( Phrase, Move ). resource_condition(lexiconT,output_form(Phrase,Move),Lexicon):- Lexicon : output_form( Phrase, Move ).

44. Explicit information state datastructure makes systems more transparent Update rules provide an intuitive way of formalising theories in a way which can be used by a system Domain knowledge encoded in resources; –the rest of the system is domain independent –resources can be switched dynamically Modular architecture promotes reuse TrindiKit Features

45. Features, cont’d Allows both serial and asynchronous systems Interfaces to OAA Generic WWW interface Runs on UNIX, Windows, Linux Needs SICStus Prolog Version 2.0 is available, next version coming soon (SIRIDUS) www.ling.gu.se/projects/trindi/trindikit Larsson & Traum: NLE Special Issue on Best Practice in Dialogue Systems Design, 2000

46. GoDiS – information state based on Questions Under Discussion (Larsson et al 2000) MIDAS – DRS information state, first-order reasoning (Bos & Gabsdil, 2000) EDIS – information state based on PTT (Matheson et al 2000) SRI Autoroute – information state based on Conversational Game Theory (Lewin 2000); robust interpretation (Milward 2000) Systems developed using TrindiKit

47. Post-TRINDI applications SIRIDUS project (EU 2000-) –command and negotiative dialogues –Spanish, Swedish –GoDiS, SRI system D’Homme (EU 2001) –Dialogues in the Home Environment –GoDiS, SRI system Instruction Based Learning for mobile robots (U Edinburgh) –MIDAS Tutoring Electricity (U Edinburgh) –EDIS, Beetle

49. ???selectors –selects an object ( Obj ) embedded in another object ( Arg ) –selector(Sel,Arg,Obj,ArgWithHole,Hole ). –e.g. selector(fst,stack([E|S]),E,stack([H| S]),H). –Every selector corresponds to a function function(Sel,[Arg],Object).

50. Datatype definitions relations –relations between objects; true or false –format: relation(Rel,Args). –Example definition: relation(fst,[stack([E|S]),E]). condition: fst($/shared/qud,Q)

51. Datatype definitions functions –functions from arguments to result –format: function(Fun,Args,Result). –Example definition: function(fst,[stack([E|S])],E). in condition: –Q = fst($/shared/qud) –Q = $/shared/qud/fst in effect: –next_move/content := fst($/shared/qud) –every function corresponds to a relation relation(Fun,[Args@[Result]]).

52. Datatype definitions (3) operations –operation(Op,InObj,Args,OutObj). –e.g. operation(push,stack(S),E,stack([E|S] )). –every operation corresponds to a relation relation(Op,[InObj|Args]@[OutObj]).

53. ???Components of a system Infostate [domain independent] –type declaration –initial state Modules [domain independent] –rules –rule application algorithms –overall control algorithm Resources [domain dependent] –incl. resource interfaces