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DALI Multiagent System Handbook and Examples. How to create and use a DALI Agent: Summary How the DALI Interpreter starts (provided you have installed.

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Presentation on theme: "DALI Multiagent System Handbook and Examples. How to create and use a DALI Agent: Summary How the DALI Interpreter starts (provided you have installed."— Presentation transcript:

1 DALI Multiagent System Handbook and Examples

2 How to create and use a DALI Agent: Summary How the DALI Interpreter starts (provided you have installed Sicstus Prolog) How to create an agent: the DALI initialization file How to write a DALI logic program Architecture of the DALI Interpreter Examples

3 How the DALI Interpreter starts In order to start the DALI Multiagent System its necessary to activate the server, next the user module, finally one or several DALI agents. active_dali.pl/ agent.bat active_dali.pl/ agent.bat active_user.pl/ user.bat active_server.pl/ server.bat...

4 How the Server starts We can activate the DALI server either by invoking the the executable file server.bat or, via the Sicstus Prolog shell, by loading the file active_server.pl. This is the command to load the server, that you can fond in the demo directory: load_files('C:/Programmi/SICStus Prolog 3.11.1/bin/demo/active_server.pl'). active_server.pl/ active_server.exe DALI program file_dali.txtactive_server.plactive_user.pl active_dali_wi.pl

5 How the User Module starts active_user.pl/ active_user.exe We can activate the DALI user module either by using the user.bat' executable file or, via the Sicstus Prolog shell, by loading the file active_user.pl. This is the command to load the file that you can find in the demo directory: load_files('C:/Programmi/SICStus Prolog 3.11.1/bin/demo/active_user.pl'). The user module opens a user window for communicating with DALI agents, as explained later on. The name of the Receiver agent The language of the message The list of terms useful to interprete a message The name of the Sender agent The content of the message

6 How the DALI Interpreter starts We can activate the DALI Interpreter either by using the executable file agent.bat. If the paths of the initialization file and of the current installation of Sicstus Prolog set in the batch file are right, the agent will be activated:.................. Actived Agent................... active_dali.pl/ agent.bat DALI logic program dali program help.txt initialization_files active_server.pl active_user.pl active_dali_wi.pl help.txt Initialization file In this way it is possible to activate several DALI agents having different names and logic programs.

7 DALI initialization file The initialization file.txt must be in the directory initialization_dali_files, and contains the following informations: The name of the file that contains the DALI logic program; The name of the agent; The adopted ontology ('no' if no ontology is used); The adopted language (Italian,English,…) in the communication acts; The name of the file containing the tell/told communication constraints; The name of the communication library; The agents abilities ( kind of work, hobbies,…) These parameters are grouped in a string with prefix agent, according to the above order, with the syntax exemplified below.

8 DALI initialization file: example Example: content of the initialization file agent('demo/program/italian',gino, '../onto/gino.onto',italian, ['demo/communication'], ['demo/communication_fipa'],[tourist]). The path is specified starting from the directory where the interpreter is.

9 DALI initialization file: example Precisely: gino is the name of the agent, italian.onto is the ontology file in the directory onto and Italian is the language spoken by the agent. Finally, communication is the file communication.con in the main directory containing the tell/told constraints and communication_fipa is the library with the fipa communications primitives. The last parameter suggests that the agent is a tourist. At this point, we can write a DALI logic program with.txt extension and put it in the directory program.

10 In the initialization string (see above) we put the initialization file under the directory 'initialization_dali_files' and the DALI logic program file file_dali.txt in the directory program: Generate a DALI initialization file DALI program file_dali.txt file_dali.onto communication_fipa.txt communication.conactive_dali_wi.pl ONTO

11 How the User Module works active_user.pl/ active_user.exe The user module allows the user to communicate with an existing DALI agents, by means of the DALI primitive send_message(Content,Sender) where Sender=user and Content is an external event we want the agent to perceive. will ask the following arguments: Insert name of addressee |: pippo. Insert From |: user. Insert message |: send_message(danger,user). The name of the Receiver agent The name of the Sender agent The content of the message

12 How to use Ontologies in the User Module (simple way, to be further developed) If we have for instance, in the DALI logic program, the following reactive rule: dangerE:>once(ask_for_help). ask_for_help:-call_policeA. call_police: { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/5/1550818/slides/slide_12.jpg", "name": "How to use Ontologies in the User Module (simple way, to be further developed) If we have for instance, in the DALI logic program, the following reactive rule: dangerE:>once(ask_for_help).", "description": "ask_for_help:-call_policeA. call_police:

13 Write DALI logic program A Dali program is a file txt whose content is a DALI program. Now we shortly recall the main features of this language by writing a DALI agent: External events: The external events are syntactically indicated by the postfix E. When an event enters the agent from its external world, she can perceive it and decide to react. The reaction is defined by a reactive rule which has in its head that external event. The special token :>, used instead of :-, indicates that the reactive rule performs forward reasoning. If we write in the txt file this simple reactive rule: alarm_clock_ringsE:>stand_upA the agent observes the following behavior. We use the user module to send to the agent the external event alarm_clock_rings.

14 Write DALI logic program:External Event Insert name of addressee |: pippo. Insert From |: user. Insert message |: send_message(alarm_clock_rings,user)................... Actived Agent................... make(stand_up) The DALI agent will do the action contained in the body of the reactive rule. Nome file: alarm.txt

15 Internal events: The internal events define a kind of individuality of a DALI agent, making her proactive independently of the environment, of the user and of the other agents, and allowing her to manipulate and revise her knowledge. An internal event is syntactically indicated by the postfix I, and its description is composed of two rules. The first one contains the conditions (knowledge, past events, procedures, etc.) that must be true so that the reaction (in the second rule) may happen. If we write in the txt file those two rules: i_am_lazy:-alarm_clock_rings P not(stand_up P ) i_am_lazy I :> i_take_a_vacation_day A. the agent exhibits the following behavior. We use the user module to send to the agent the past event alarm_clock_rings P but this past event could be the past form of the external event as specified in the previous paragraph, and arrived before. Write DALI logic program:Internal Event

16 Write DALI logic program:External Event Insert name of addressee |: pippo. Insert From |: user. Insert message |: confirm(alarm_clock_rings,user)................... Actived Agent................... make(i_take_a_vacation_day) The DALI agent will make the action contained in the reaction of the internal event. Nome file: alarm_clock.txt

17 Present events: When an agent perceives an event from the external world it does not necessarily react to it immediately: she has the possibility of reasoning on the event, before (or instead of) triggering a reaction. Reasoning also allows a proactive behavior. In this situation, the event is called present event and is indicated by the suffix N. arrives_someone:-bell_ringsN. arrives_someoneI:>get_dressedA. get_dressed:< get_undressedP. bell_ringsE:>open_the_doorA. In this case, when we send the external event bell_rings to the agent, she makes the actions get_dressed and open_the_door if the internal event has been processed before the external event. Else, she does only the action open_the_door. In small DALI programs is unlikely to observe the reaction to the internal event, because the processing of the external events is faster and the interpreter, after the action open_the_door, erases the reaction to the internal event. Write DALI logic program:Present Event

18 Write DALI logic program:Present Events Insert name of addressee |: pippo. Insert From |: user. Insert message |: send_message(bell_rings,user)................... Actived Agent................... make(open_the_door) make(get_dressed) make(open_the_door) Nome file: wear.txt

19 Actions: Write DALI logic program:Actions Simple actions: The action in the DALI program is specified as actionA. For example i_go_to_bedA, i_take_the_busA, … When the agent does an action, on the prolog shell you can observe make(action). Messages as actions: From a DALI program, a message can be sent by writing: messageA(To, Content) where To is the name of the agent that must receive the communication act and Content is the DALI/FIPA primitive.

20 Write DALI logic program:Actions We now describe the primitives used in a DALI program. Sender is the agent that sends the message. o send_message(External_event, Sender) this primitive is used to call an external event within a reactive rule; o confirm(Assertion, Sender) this primitive is used to assert a fact within a DALI agent; o disconfirm(Assertion, Sender) this primitive is used to retract a fact within a DALI agent; o propose(Action, List_Conditions,Sender) this primitive is used to propose an agent to do an action contained within a DALI program. The agent can respond by accepting to do the action (accept_proposal) or by rejecting the proposal (reject_proposal) if the conditions in the message are false. When the agent decides to make the action, she verifies if the conditions of the action rule are true. In this case, the agent does the action or else she sends to the other agent a failure message.

21 Write DALI logic program:Actions o execute_proc(Head, Sender) this primitive is used to invoke the head of a generic rule (procedure) in the DALI program; o query_ref(Fact, N, Sender) this primitive is used to answer an agent on some information about a not ground Fact. N is the number of the requested matchings; o agree(Fact, Sender) this primitive is used to answer an agent knowing a ground Fact; o cancel(Action, Sender) this primitive is used to communicate to an agent to cancel a requested action. Also in this case, it is difficult to see the effect of this primitive because the agent does immediately the action. To see the effect, the queue of actions must contain several items.

22 A goal is an objective that an agent must reach. In the DALI language, a goal is a particular internal event that the interpreter begins to attempt when it is invoked. The goal has a postfix G. Write DALI logic program: Goals PLANNER Goal Environment State Actions Plan to reach a goal...,goal1G,... goal1:- condition 11,...,condition 1k subgoal 11 G,...,subgoal 1N G, subgoalP 11,...,subgoalP 1N.... goal1:-condition m1,...,condition mk subgoalG m1,...,subgoalG mN, subgoalP 11,...,subgoalP 1N. goal1I:>action 1,...,goal2G,...,action k. How it works:

23 Write DALI logic program: Goals We consider a simple example: an agent must wear socks and shoes. goE:>put_shoesG. put_shoes:- put_right_shoeG,put_left_shoeG,right_shoe_onP, left_shoe_onP. put_shoesI:>left_and_right_shoes_onA, retractall(past(_,_,_)). put_right_shoe:-put_right_sockG,right_sock_onP. put_right_shoeI:>right_shoe_onA. put_left_shoe:-put_left_sockG,left_sock_onP. put_left_shoeI:>left_shoe_onA. put_right_sock:-have_right_sockP. put_right_sockI:>right_sock_onA. put_left_sock:-have_left_sockP. put_left_sockI:>left_sock_onA.

24 Write DALI logic program: Goals Insert name of addressee |: pippo. Insert From |: user. Insert message |: confirm(have_left_sock,user)................... Actived Agent................... make(right_sock_on) make(right_shoe_on) make(left_sock_on) make(left_shoe_on) make(left_and_right_shoes_on) Insert name of addressee |: pippo. Insert From |: user. Insert message |:confirm(have_right_sock,user). Insert name of addressee |: pippo. Insert From |: user. Insert message |: send_message(go,user). Nome file: shoes.txt

25 Write DALI logic program: Past events past(rain,timestamp, user) is recorded within DALI shell. This past event is called using the string with postfix P. For example, rainP. Past events: A past event, indicated by the suffix P, is: o an external or internal event after a reaction; o an executed action; o a reached goal or subgoal; o a fact communicated using a confirm primitive. Insert name of addressee |: pippo. Insert From |: user. Insert message |: confirm(rain,user).

26 Processing Events Actions Goals Pre-processingfile.txt Communication module Communication module The architecture of a DALI agent

27 The files that the interpreter generates from DALI txt file file.txt file.ple file.plf file.pl The DALI interpreter generates some auxiliary files for each agent. These files are put in the same directory as the txt DALI file.

28 dangerE:>once(ask_for_help). ask_for_help:-call_policeA. call_police:go_to_bathroomA, close_the_doorA. go_out:-dangerP,screamP. go_outI:>go_to_neighbourA. Reaction rule External event Past event Action Internal event Action rule A simple txt DALI file We use this txt file to show how the interpreter works creating ple, plf and pl files. In order to show the naming process we use a new example containing variables.

29 What the Interpreter records in the ple file [danger]. [remain_at_home,go_out,external_refused_action_propose(A,Ag), refused_message(AgM,Con)]. [call_police,scream,go_to_bathroom,close_the_door,go_to_neighbour,message(Ag,in form(query_ref(X,N),values(L),A)),message(Ag,refuse(query_ref(variable),motivatio n(refused_variables),A)),message(Ag,inform(query_ref(X,N),motivation(no_values), A)),message(Ag,inform(agree(X),values(yes),A)),message(Ag,inform(agree(X),value s(no),A))…]. [call_police]. []. External events Internal events Actions Conditions Present events Goals to reach Goals to test This file is used by the interpreter to manage the behavior of the agent through the classes of the events, the actions, goals,…

30 eve(predator_attacks(var_X)):- once(try_to_escape(var_X)). try_to_escape(var_X):- a(fly(var_X)). try_to_escape(var_X):- a(run(var_X)). cd(fly(var_X)):- evp(bird(var_X)), not(evp(abnormal(var_X))). The naming of variables in the pl file The interpreter generates a pl file where all rules are subjected to naming process. All variables has been transformed to costants using the suffix var_. predator_attacksE(X):> once(try_to_escape(X)). try_to_escape(X):-flyA(X). try_to_escape(X):-runA(X). fly(X): { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/5/1550818/slides/slide_30.jpg", "name": "eve(predator_attacks(var_X)):- once(try_to_escape(var_X)).", "description": "try_to_escape(var_X):- a(fly(var_X)). try_to_escape(var_X):- a(run(var_X)). cd(fly(var_X)):- evp(bird(var_X)), not(evp(abnormal(var_X))). The naming of variables in the pl file The interpreter generates a pl file where all rules are subjected to naming process. All variables has been transformed to costants using the suffix var_. predator_attacksE(X):> once(try_to_escape(X)). try_to_escape(X):-flyA(X). try_to_escape(X):-runA(X). fly(X):

31 The directives of plf file We use this file to set some parameters that determine the behavior of the agent relatively to external, internal, past events and actions. External event We can decide if an external event must be processed with a normal or high priority: external_event(Event,normal). external_event(Event,high). Past event We can decide how long or until which condition a past event must be kept in the memory of an agent: past_event(Event,Seconds). (the past event is kept in memory some Seconds) past_event(Event,forever). (the past event is kept in memory forever) past_event(Event,until(Cond)). (the past event is kept in memory until Condition) Action We can decide if an action must be processed with a normal or high priority: action(Action,normal). action(Action,high). Action/Message We can decide if to submit a message to tell the tell check: mod(Action, check).

32 The directives of plf file Now we examine the directives on internal events. Internal event We can set several parameters for an internal event in order to tune the Interpreter behaviour: o the frequency(seconds) with which the interpreter attempts the internal event; o how many times the agent must react if the internal event is true (1,2,..,forever); o when the agent must react: this parameter is true if the reaction must happen forever or else we can link the reaction to some past events belonging to body of the first rule of the internal event; when the past event inside a change list is modified the agent will be able to react again. For example, if we have the internal event: think:-rainP, go_outP,buy_umbrellaP. thinkI:>open_the_umbrellaA. we can set parameters as: internal_event(think,3,1,change([rain,go_out]),forever). o when/until when the interpreter must attempt the internal event: o until_date(Date): till certain date; o until_cond(Condition): when the Condition is false; o forever: forever

33 Some directives of plf example file action(call_police,normal). action(scream,normal). action(go_to_bathroom,normal). action(close_the_door,normal). action(go_to_neighbour,normal). external_event(danger,normal). past_event(danger,20). past_event(remain_at_home,20). past_event(go_out,20). past_event(call_police,20). past_event(scream,20). past_event(go_to_bathroom,20). past_event(close_the_door,20). past_event(go_to_neighbour,20). internal_event(remain_at_home,3,forever,true,until_cond(past(remain_at_home))). internal_event(go_out,3,forever,true,until_cond(past(go_out))). mod(message(_,inform(_,motivation(refused_message),_)),check). The action is put in the queue with normal priority This past event is kept in memory 20 seconds This internal event is attempted every 3 seconds The agent will react forever We specify no conditions This internal event is attempted until the past event remain_at_home becomes true This message is submitted to tell check

34 The Communication architecture META LEVEL DALI INTERNAL INTERPRETER TELL CHECK TOLD CHECK Incoming message Outcoming message The message passes this level only if the corresponding told rule is true. If the agent doesnt know the content of the message, she calls the meta-level and uses the ontology and/or other properties in order to understand the communication act. The message, submitted to tell check, is sent only if the corresponding tell rule is true.

35 The Told Check level TOLD CHECK Incoming message Each DALI agent has a con file, specified in the initialization file, that contains the told/tell rules. These rules, external to interpreter, can be modified by the user. The structure of a told rule is: told(Sender,Content):-constraint 1,…,constraint n. In this example, an agent receives a message, using the primitive send_message, only if the Sender agent isnt an enemy: told(Ag,send_message(_)):-not(enemyP(Ag)). A message that does not go through the told level is eliminated. The agent Sender receives an inform message asserted as a past event.

36 The Meta-Level Each DALI agent uses an (optional) meta procedure written in the communication.con file that specifies how the entity can interprete an unknown message. This procedure can be modified by the user. In the initialization file the user can specify the ontology file that contains informations about the ontology that the agent must use. This file contains informations about the location of the ontology ( remember that ontologies are used by means of Sesame semantic repositories ). "PREFIX rdfs: ". Prefixes of namespaceshttp://www.w3.org/2000/01/rdf-schema "/openrdf-sesame/repositories/Ontology". Location of the ontology "localhost:8080". Location of Tomcat ( On which runs SESAME ). META LEVEL

37 The Tell Check level The user can set the mod string in the plf file in order to submit a message to tell check. In this case, the message is actually sent only if the corresponding tell rule is true. The tell rules can be modified by the user. The structure of a tell rule is: tell(Receiver,Sender,Content):-constraint 1,…,constraint n. In this example, an agent sends a message, using the primitive send_message, only if she has a trust greater than 4 in the Receiver agent: tell(To,_,send_message(_)):-trustP(_,To,N),N>4. A message that does not go through the tell level is eliminated. TELL CHECK Outcoming message

38 Examples – A dangerous situation… One Agent!

39 Examples – A dangerous situation… Initialization file name: help.txt DALI logic file name: help.txt DALI program help.txt active_server.plactive_user.pl active_dali.plhelp.txt initalization_files

40 Examples – A dangerous situation… dangerE:>once(ask_for_help). ask_for_help:-call_policeA. call_police:go_to_bathroomA, close_the_doorA. go_out:-dangerP,screamP. go_outI:>go_to_neighbourA. DALI logic program help.txt

41 Examples – A dangerous situation… Run the DALI logic program.................. Actived Agent................... make(scream) make(go_to_neighbour) Insert name of addressee |: pippo. Insert From |: user. Insert message |: send_message(danger,user).

42 Examples – A dangerous situation… If the agent has a phone….................. Actived Agent................... make(call_police) make(go_to_bathroom) make(close_the_door) New message Insert name of addressee |: pippo. Insert From |: user. Insert message |: confirm(have_a_phone,user). New message Insert name of addressee |: pippo. Insert From |: user. Insert message |: send_message(danger,user). she reacts differently!

43 Two Agents! Examples – Error Recovery planning…

44 Initialization file name: recovery.txt and sensor.txt DALI logic file name: recovery.txt and sensor.txt DALI program recovery.txtactive_server.plactive_user.pl active_dali.plrecovery.txt sensor.txt initalization_files

45 Examples – Error Recovery planning… DALI logic program recovery.txt error_recovery(M,M1):- go_rightP(_,M),goal(M),informP(reality(M,M1),sensor),M\=M1. error_recovery(M,M1):- go_leftP(_,M),goal(M),informP(reality(M,M1),sensor),M\=M1. error_recovery(M,M1):- go_forwardP(_,M),goal(M),informP(reality(M,M1),sensor),M\=M1. error_recoveryI(M,M1):>recovery_errorA(M,M1),drop_pastA(reality(M,M1)). reached_goal(M):-go_rightP(_,M),goal(M). reached_goal(M):-go_leftP(_,M),goal(M). reached_goal(M):-go_forwardP(_,M),goal(M). reached_goalI(M):>clause(agent(Ag),_), messageA(sensor,send_message(what_about_my_position(M,Ag),Ag)). … right(exit1,bank1). right(exit2,bank2). left(bank1,hospital1). forward(bank2,bank1). goal(hospital1).

46 Examples – Error Recovery planning… DALI logic program sensor.txt what_about_my_positionE(M,Ag):>once(examine_position(M,Ag,_)). examine_position(M,Ag,M1):- messageA(Ag,inform(reality(M,M1),sensor)),wrong_positionA(M,Ag). message(_,inform(reality(M,M1),sensor)): { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/5/1550818/slides/slide_46.jpg", "name": "Examples – Error Recovery planning… DALI logic program sensor.txt what_about_my_positionE(M,Ag):>once(examine_position(M,Ag,_)).", "description": "examine_position(M,Ag,M1):- messageA(Ag,inform(reality(M,M1),sensor)),wrong_positionA(M,Ag). message(_,inform(reality(M,M1),sensor)):

47 Error Recovery planning STATION Exit 2 Exit 1 Bank 2 Bank 1 Hospital The environment…

48 Error Recovery planning STATION Exit 2 Exit 1 Bank 2 Bank 1 Hospital First situation: the agent exits from Exit 1 and goes to Hospital 1 confirm(i_am_at_exit(exit1),user) make(go_right(exit1,bank1)) make(go_left(bank1,hospital1))

49 Run the DALI logic programs recovery.txt and sensor.txt.................. Actived Agent................... make(go_right(exit1,bank1)) make(go_left(bank1,hospital1)) send_message_to(sensor,send_message(what_about_my_position(hospital1,pippo), pippo),italian,[]) Insert name of addressee |: pippo. Insert From |: user. Insert message |: confirm(i_am_at_exit(exit1),user). Examples – Error Recovery planning….................. Actived Agent................... make(right_position(hospital1,pippo)) robot pippo sensor

50 Error Recovery planning STATION Exit 2 Exit 1 Bank 2 Bank 1 Hospital make(go_right(exit2,bank2)) make(go_forward(bank2,bank1)) make(go_left(bank1,hospital1)) Second situation: the agent exits from Exit 2 and goes to Hospital 1 confirm(i_am_at_exit(exit2),user)

51 Run the DALI logic programs recovery.txt and sensor.txt.................. Actived Agent................... make(go_right(exit2,bank2)) make(go_forward(bank2,bank1)) make(go_left(bank1,hospital1)) send_message_to(sensor,send_message(what_about_my_position(hospital1,pippo), pippo),italian,[]) Insert name of addressee |: pippo. Insert From |: user. Insert message |: confirm(i_am_at_exit(exit2),user). Examples – Error Recovery planning….................. Actived Agent................... make(right_position(hospital1,pippo)) robot pippo sensor

52 Error Recovery planning STATION Exit 2 Exit 1 Bank 2 Bank 1 Hospital 1 Third situation: the agent thinks to be at Exit 1 while really she is at Exit 2. When she is at Hospital 1 /Bank 2 a planner recognizes the error and modifies the plan. make(go_right(exit1,bank1)) make(go_left(bank1,hospital1)) make(recovery_error(hospital1,bank2)) make(go_forward(bank2,bank1)) make(go_left(bank1,hospital1)) ? Hospital 1

53 Run the DALI logic programs recovery.txt and sensor.txt.................. Actived Agent................... Insert name of addressee |: sensor. Insert From |: user. Insert message |: confirm(error(hospital1,bank2),user). Examples – Error Recovery planning… (step1) sensor

54 Run the DALI logic programs recovery.txt and sensor.txt Insert name of addressee |: sensor. Insert From |: user. Insert message |: confirm(i_am_at_exit(exit1),user). Examples – Error Recovery planning… (step2).................. Actived Agent............... send_message_to(pippo,inform(reality(hospital1, bank2),sensor),italian,[]) make(wrong_position(hospital1,pippo)) sensor.................. Actived Agent................... make(go_right(exit1,bank1)) make(go_left(bank1,hospital1)) send_message_to(sensor,send_message(what_about_my_position(hospital1,pippo),pippo), italian,[]) make(recovery_error(hospital1,bank2)) make(go_forward(bank2,bank1)) make(go_left(bank1,hospital1)) robot pippo

55 Two Agents! Examples – Informations and Meta-reasoning…

56 Initialization file name: agent1.txt and agent2.txt DALI logic file name: agent1.txt and agent2.txt DALI program agent2.txt initialization_files active_server.plactive_user.pl active_dali_wi.pl agent2.txt agent1.txt Examples – Informations and Meta-reasoning…

57 DALI logic program agent1.txt rainE:-open_the_umbrellaA. Examples – Informations and Meta-reasoning… DALI logic program agent2.txt i_am_illE:>go_to_family_doctorA. We will consider two simple agents. We are interested in showing how the communication primitives query_ref and agree use the meta-level reasoning.

58 Examples – Informations and Meta-reasoning… We will communicate to agent1 the fact ama(james,julia). In the ontology that the agent pippo adopts there is the fact: ontology(pippo,ama,love). Run the DALI logic program agent1.txt Insert name of addressee |: pippo. Insert From |: user. Insert message |: confirm(ama(james,julia),user).

59 Examples – Informations and Meta-reasoning… Agent2 will ask agent1 about the james/julia love. The agent2 pino will use the communication primitives query_ref and agree. Run the DALI logic program agent2.txt Insert the path and the name of the initialization file: |: 'demo/agent2.txt'. New message Insert name of addressee |: pippo. Insert From |: pino. Insert message |: query_ref(ama(julia,Y),1,pino)................... Actived Agent................... send_message_to(pino,inform(query_ref(ama(julia,fdvar_9),1),values([ama(james,julia)]), pippo),italian,[]) (fdvar is the reification method of the Sicstus Prolog)

60 Examples – Informations and Meta-reasoning… New message Insert name of addressee |: pippo. Insert From |: pino. Insert message |: query_ref(love(julia,Y),1,pino)................... Actived Agent................... send_message_to(pino,inform(query_ref(love(julia,fdvar_10),1),values([ama(james,julia)]), pippo),italian,[])

61 Examples – Informations and Meta-reasoning… New message Insert name of addressee |: pippo. Insert From |: pino. Insert message |: agree(love(julia,james),pino)................... Actived Agent................... send_message_to(pino,inform(agree(love(julia,james)),values(yes),pippo),italian,[])

62 Three Agents! Examples – Cooperation and Ontology…

63 Initialization file name: italian.txt, english.txt and translator.txt DALI logic file name: italian.txt, english.txt and translator.txt Examples – Cooperation and Ontology… demo progra m english.txt initialization_files active_server.pl active_user.pl active_dali_wi.pl english.txt italian.txt translator.txt italian.txt

64 DALI logic program italian.txt questionE(Q,L,M):>agente(A,_,_,_), once(examine_question(Q,L,M,A)). examine_question(Q,_,M,A):-messageA(M,send_message(know(Q,A),A)). message(_,send_message(know(Q,A),A)): { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/5/1550818/slides/slide_64.jpg", "name": "DALI logic program italian.txt questionE(Q,L,M):>agente(A,_,_,_), once(examine_question(Q,L,M,A)).", "description": "examine_question(Q,_,M,A):-messageA(M,send_message(know(Q,A),A)). message(_,send_message(know(Q,A),A)):

65 DALI logic program italian.txt questionE(Q,L,M):>agente(A,_,_,_), once(examine_question(Q,L,M,A)). examine_question(Q,_,M,A):- messageA(M,send_message(know(Q,A),A)). message(_,send_message(know(Q,A),A)): { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/5/1550818/slides/slide_65.jpg", "name": "DALI logic program italian.txt questionE(Q,L,M):>agente(A,_,_,_), once(examine_question(Q,L,M,A)).", "description": "examine_question(Q,_,M,A):- messageA(M,send_message(know(Q,A),A)). message(_,send_message(know(Q,A),A)):

66 DALI logic program english.txt questionE(Q,L,M):>agente(A,_,_,_), once(examine_question(Q,L,M,A)). examine_question(Q,_,M,A):- messageA(M,send_message(know(Q,A),A)). message(_,send_message(know(Q,A),A)): { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/5/1550818/slides/slide_66.jpg", "name": "DALI logic program english.txt questionE(Q,L,M):>agente(A,_,_,_), once(examine_question(Q,L,M,A)).", "description": "examine_question(Q,_,M,A):- messageA(M,send_message(know(Q,A),A)). message(_,send_message(know(Q,A),A)):

67 DALI logic program translator.txt translateE(Q,L,M,A):>once(examine_translation(Q,L,M,A)). examine_translation(Q,_,M,A):-clause(translated(Q,Tr),_), messageA(A,send_message(question(Tr,italian,M),translator)). examine_translation(Q,_,M,A):-translatedP(Q,Tr), messageA(A,send_message(question(Tr,italian,M),translator)). examine_translation(Q,_,M,A):-clause(translated(Tr,Q),_), messageA(A,send_message(question(Tr,english,M),translator)). … translated(i,io). translated(love,amo). translated(hate,odio). translated(you,te). Examples – Cooperation and Ontology…

68 ITALIAN TRANSLATOR Cooperation and Ontology ITALIANENGLISH questionE(Term,Language,From) know(i,susy). know(love,susy). know(hate,susy). know(you,susy). know(io,gino). know(amo,gino). know(odio,gino). know(te,gino). translated(i,io). translated(love,amo). translated(hate,odio). translated(you,te). The environment…

69 ITALIAN Cooperation and Ontology ITALIANENGLISH know(io,_) know(amo,_) know(te,_) know(i,_) know(love,_) know(you,_) evviva_loves_me(susy)

70 Run the DALI logic programs italian.txt Examples – Cooperation and Ontology… Insert name of addressee |: gino. Insert From |: susy. Insert message |: send_message(question(i,english,susy),susy). Insert name of addressee |: gino. Insert From |: susy. Insert message |: send_message(question(love,english,susy),susy). Insert name of addressee |: gino.. Insert From |: susy. Insert message |: send_message(question(you,english,susy),susy).

71 .................. Actived Agent............... make(comprehension) english/susy.................. Actived Agent................... send_message_to(gino,send_message(question(io,italian,susy),translator),italian,[]) send_message_to(gino,send_message(question(amo,italian,susy),translator),italian,[]) send_message_to(gino,send_message(question(te,italian,susy),translator),italian,[]) Examples – Cooperation and Ontology….................. Actived Agent............... send_message_to(translator,send_message(translate(i,english,susy,gino),gino), italian,[]) send_message_to(susy,send_message(know(io,gino),gino),italian,[]) send_message_to(translator,send_message(translate(love,english,susy,gino),gi no),italian,[]) send_message_to(susy,send_message(know(amo,gino),gino),italian,[]) send_message_to(translator,send_message(translate(you,english,susy,gino),gin o),italian,[]) send_message_to(susy,send_message(know(te,gino),gino),italian,[]) make(evviva_loves_me(susy)) italian/gino translator

72 ITALIAN Cooperation and Ontology ITALIANENGLISH know(io,_) know(odio,_) know(te,_) know(i,_) know(hate,_) know(you,_) i_will_not_speak_with(susy) add_pastA(enemy(susy)) told(Ag,send_message(_)):-not(enemyP(Ag)). know(you,_) Eliminated message

73 Examples – Cooperation and Ontology… Insert name of addressee |: gino. Insert From |: susy. Insert message |: send_message(question(i,english,susy),susy). Insert name of addressee |: gino. Insert From |: susy. Insert message |: send_message(question(hate,english,susy),susy). Insert name of addressee |: gino. Insert From |: susy. Insert message |: send_message(question(you,english,susy),susy).

74 ........ Actived Agent........ make(comprehension) english/susy............. Actived Agent.......... send_message_to(gino,send_message( question(te,italian,susy),translator),itali an,[]) … Examples – Cooperation and Ontology….................. Actived Agent............... send_message_to(translator,send_message(translate(you,english,susy,gino),gin o),italian,[]) send_message_to(susy,send_message(know(te,gino),gino),italian,[]) send_message_to(translator,send_message(translate(i,english,susy,gino),gino), italian,[]) send_message_to(susy,send_message(know(io,gino),gino),italian,[]) send_message_to(translator,send_message(translate(hate,english,susy,gino),gi no),italian,[]) send_message_to(susy,send_message(know(odio,gino),gino),italian,[]) make(i_will_not_speak_with(susy)) Eliminated message:conditions not verified for send_message(question(hate,english,susy),susy) From:susy:arianna:1075Language:italianOntology:[] send_message_to(susy,inform(send_message(question(hate,english,susy),susy),motivation(refused_message),gino),italian,[]) italian/gino translator

75 ITALIAN ENGLISH Cooperation and Ontology send_message(give_present(A),A) (the filter accepts the messages as give_present(_)) accept_presentA, drop_pastA(enemy(A)) Susy,after the present, isnt an enemy and the communication is again authorized by the filter.

76 Examples – Cooperation and Ontology….................. Actived Agent............... make(accept_present) send_message_to(translator,send_message(translate(hate,english,susy,gino),gi no),italian,[]) send_message_to(susy,send_message(know(odio,gino),gino),italian,[]) recovery_friendship(Ag):-informP(_,motivation(refused_message),Ag). recovery_friendshipI(Ag):>clause(agent(A),_), messageA(Ag,send_message(give_present(A),A)). italian/gino.................. Actived Agent............... send_message_to(gino,send_message(give_present(susy),susy),italian,[]) make(comprehension) english/susy


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