Social Agents for Learning in Virtual Environments - GALA2016

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  • Social Agents for Learning in Virtual Environments

    Agnese Augello1, Manuel Gentile2 , Frank Dignum31ICAR - National Research Council of Italy,

    2ITD - National Research Council of Italy3Utrecht University, The Netherlands

  • Outline

    Learning social and communication skills

    Social skills training and SGs

    The proposed solution: SALVE

    Architecture

    Some examples

  • Why social skills?

    interpersonal, social and

    communicative competences

    social, psychological

    and occupational well-being are

    ensured by

    academic or professional success are predicted by

  • Social skills training theories

    Behavioral shaping Skinner

    Psychotherapy by Reciprocal Inhibition Wolpe

    Assertion or assertiveness training

    Wolpe & Lazarus

    Social learning theory Bandura

  • A classical social skills training procedure

    Assessment

    Direct Instruction and Coaching

    Modeling

    Role PlayingHomework assignment & Follow-up

  • Role Playing

    to practice the desired behaviours in a controlled setting

    problemsdifficult expensive

    Serious games

  • e.g. Scripted based design

    Social and communication skills training & SG

    Behavioural oriented Serious

    Games

    Behavioural oriented Serious

    Games Design

    Skinner

    Wolpe

    Wolpe & Lazarus

    Bandura

  • Behavioural oriented Serious Games Design

    Pros Cons

    Knowledge design and

    reuse

    The organization of the interaction facilitates the

    designof the scenariohides the knowledge at its base

    Interaction with the

    virtual agentThere is a fine control of the

    scenario (e.g. the conversation)

    The agent behaviour are predetermined and the

    interaction becomes repetitive after few uses.

    Player Experience

    Specific user's behaviours can be trained

    Players have no freedom. The game experience is quite different from a real one

  • Role of social context in conversation in communication

    The dialogue is a joint activity that must consider both individual and social processes

    Different communication strategies can be used according to the specific social context

    The same sentence can be used with a different meaning in different context and can raise different social effects

    You should take a cat

  • A different approach to implement the conversational agent: SALVE

    Putting social practices at the heart of the deliberation allows for more efficient

    planning (Dignum and Dignum, 2014)

    Social Agents for Learning in Virtual Environments

  • The social practice model

  • Chatbot as a possible solution?

    1966 Eliza

    1988 Jabberwacky

    1992 - Dr. Sbaitso

    1995 - A.L.I.C.E.

    2001 - Activebuddys Smarterchild

    2011 - Watson, Siri

    2012 - Google Now

    2015 - Amazon Alexa , Microsoft Cortana

    2016 More than 18.000 Bots on Im, Messanger and Facebook

  • Chatbot as a possible solution?

    Strength It is possible to quickly create a

    conversational agent, avoiding natural language processing issues

    It is easy to define the chatbotbehaviour through the design of proper question answers modules (Alice -> AIML categories)

    Weaknesses Chatbots lacks the ability to keep an

    overview and a structure of the entire conversation.

    In AIML the dialogue is managed keeping track of the last conversation exchange and setting conversation topics.

    It is difficult to design chatbots able to correctly manage social conversational practices.

    MY NAME IS *

    HELLO THERE WHAT IS YOUR NAMENice to meet you

  • Architecture of the SALVE system

  • Architecture of the SALVE system

    Using chatbot just as aninteraction interfaceExtend the AIML language thatdescribes the chatbot ruleswith social tags such that itkeeps track where it is in thesocial practice (towards state based dialogue)

  • Architecture of the SALVE system

    Integrate chatbot with a rulebased engine (DROOLS) tokeep track of the agent statesand guide it the socialpractice

  • How social practice guides SG design

  • How social practice guides SG design

  • How social practice guides SG design

    start end

    greetings

    present

    Get patientdata

    Determinesymptoms

    Determinetreatment

    Communicate!

  • How social practice guides SG design

    start end

    greetings

    present

    Get patientdata

    Determinesymptoms

    Determinetreatment

  • Examples of S-AIML

  • Example rules: Timely greetingslead to positive emotions

    rule "GreetingsReceivedInTime"

    when

    $startScene:EnterScene(scene.name=="greetings")

    $g:GreetingsReceived(this after[0ms,20000ms] $startScene )

    then

    controller.print($startScene.getScene().getName());

    controller.print("greeting received in the first 20 seconds after the start of the scene");

    OOCHappenedEvent he=new OOCHappenedEvent();

    don(he,DesirableEvent.class);

    don(he,ProspectedRelevantEvent.class);

    insert(he);

    controller.print("greeting marked as happened desirable prospected event");

    insert(new ChangeOfSceneFromGoal());

    end

  • Example rules: Timely greetingslead to positive emotions

    rule "GreetingsReceivedInTime"

    when

    $startScene:EnterScene(scene.name=="greetings")

    $g:GreetingsReceived(this after[0ms,20000ms] $startScene )

    then

    controller.print($startScene.getScene().getName());

    controller.print("greeting received in the first 20 seconds after the start of the scene");

    OOCHappenedEvent he=new OOCHappenedEvent();

    don(he,DesirableEvent.class);

    don(he,ProspectedRelevantEvent.class);

    insert(he);

    controller.print("greeting marked as happened desirable prospected event");

    insert(new ChangeOfSceneFromGoal());

    end

    rule "DesirableEventHappened"when

    OOCHappenedEvent(this isAProspectedIrrelevantEvent,this isA DesirableEvent)

    $agent:Emotion(this isA Agent)then

    controller.print("captured desirable event");$agent.setJoy($agent.getJoy()+1);controller.print("increase joy");controller.setJoy($agent.getJoy());

    end

  • Example rules: Greetings not received in time lead to negative emotions

    rule "GreetingsNotReceivedInTime"

    when

    $startScene:EnterScene(scene.name=="greetings")

    (not(GreetingsReceived(this after[0ms,20000ms] $startScene ))

    then

    controller.print("greeting not received in the first 20 seconds after the start of thescene");

    OOCNotHappenedEvent nhe=new OOCNotHappenedEvent();

    don(nhe,DesirableEvent.class);

    don(nhe,ProspectedRelevantEvent.class);

    insert(nhe);

    controller.print("dummy event marked as not happened desirable prospected event");

    controller.respond("why you did not say hello!");

    end

  • Example rules: Greetings not received in time lead to negative emotions

    rule "GreetingsNotReceivedInTime"

    when

    $startScene:EnterScene(scene.name=="greetings")

    (not(GreetingsReceived(this after[0ms,20000ms] $startScene ))

    then

    controller.print("greeting not received in the first 20 seconds after the start of thescene");

    OOCNotHappenedEvent nhe=new OOCNotHappenedEvent();

    don(nhe,DesirableEvent.class);

    don(nhe,ProspectedRelevantEvent.class);

    insert(nhe);

    controller.print("dummy event marked as not happened desirable prospected event");

    controller.respond("why you did not say hello!");

    end

    rule "DesirableProspectedEventNotHappened"when

    $d:OOCNotHappenedEvent(this isA ProspectedRelevantEvent, this isA DesirableEvent)

    $agent:Emotion(this isA Agent)then

    controller.print("captured not happened desirable event");$agent.setDisappointment($agent.getDisappointment()+1);controller.print("increased Disappointment");controller.setDisappointment($agent.getDisappointment());

    end

  • Empathic opportunities are givenand can be taken or ignored

  • SALVE architecture

  • SALVE architecture

  • SALVE architecture

  • SALVE architecture

  • Conclusion and future work 1/2

    The proposed solution:puts social practice at the heart of the deliberative process of

    an agent;allows for a dynamic activation of categories, depending on the

    current social practice, the pursued plan, the on-going activity, and finally, at the lowest level the agents identity;

    allows for a great flexibility in the conversation while at the same time simplifying the formalization of the chatbot KB;

    ensures to the player a greater freedom in sentences expression, and the possibility to experiment dynamic scenarios and different roles;

    Lets the player actively create a conversation rather than choose moves

  • Conclusion and future work 2/2

    Future work:finalize the implementation of the serious game according to a proper learning design approach;Improve the social practices representations;create a tool to support the designervalidate the proposed approach

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