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Presentation on NPCs and language learning in Second Life

Presentation on NPCs and language learning in Second Life

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  • 1. Presented by …… Scott Grant, Chinese Studies Program The role of non-player characters (bots) in task-based language and culture learning
  • 2. What are chat bots? virtual agents, interactive virtual agents (IVA), brand agents, branded agents, virtual assistants, artificial conversational entities, virtual employees, conversational agents, embodied conversational agents (ECA), chatterbots, conversational systems, chatterbox, virtual chat agents, or chat bots
  • 3. What are chat bots? A chatbot (or chatterbot, or chat bot) is a computer program designed to simulate an intelligent conversation with one or more human users via auditory or textual methods. Traditionally, the aim of such simulation has been to fool the user into thinking that the program's output has been produced by a human (the Turing test).
  • 4. What are chat bots? An artificial living entity designed to have conversations with real human beings. That can be a text conversation via computers, a spoken conversation or even a non-verbal conversation.
  • 5. Chat bots and AI
    • Strong AI
    • Searle: “ The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds.” ( )
    • Current usage: “ An artificial intelligence system can think ( or  act like it thinks)  as well as or better than people do . ”
    • ( )
  • 6. Chat bots and AI
    • Weak AI
    • Searle: “ An artificial intelligence system can (only)  act like  it thinks and has a mind.”
    • Current usage: “An artificial intelligence system which is not intended to match or exceed the capabilities of human beings”
  • 7. Chat bots and ‘weak AI’
    • Historical chat bots like ELIZA and ALICE operate on the basis of the recognition of key words or phrases (patterns) in the input and when matched respond with pre-programmed output / responses that move the conversation along in a seemingly ‘intelligent’ way.
    • Since the mid 90s many chat bots have been based on AIML, a mark-up language developed by Dr Richard Wallace that is based on key-word or ‘pattern’ matching.
  • 8. AIML (Artificial Intelligence Mark-up Language)
    • AIML, or Artificial Intelligence Mark-up Language, is an XML dialect for creating natural language software agents.
      • ( )  
    • AIML was originally adapted from a non-XML grammar also called AIML, and formed the basis for the first Alicebot, A.L.I.C.E., the Artificial Linguistic Internet Computer Entity. ( )
  • 9. Chat bot roles
    • Entertainment
      • Early chat bots were primarily designed for the purpose of general, broad-ranging conversations that attempted to simulate human conversation, but became circular and meaningless fairly quickly
    • Commerce and service industries
      • Chat bots are now more and more commonly being used as information retrieval systems in both commercial and non-commercial organisations where they act as an initial customer interface that can provide answers/information (in text and voice) to FAQs within a fairly narrowly defined scope
  • 10. Chat bot roles
    • Games
      • Blue Mars
      • Advanced Reality chat bot
      • ( )
    • Education
      • Language learning
      • atmospheric science outreach and education
      • ( )
  • 11. Chat bot architecture – 2D Web and 3D VWs
    • AIML chat bot interpreter program + 2D or 3D interface
    • 2D interfaces often consist of cartoon or realistic human faces (and sometimes animals or machines) linked with chat bot program and embedded on webpage
    • 3D interfaces in VWs like Second Life can be:
      • Prim-bots (connected by LSL scripts)
      • Avatar-bots (connected in a variety of ways)
  • 12. AIML interpreter programs
    • Pandorabots
      • ( )
    • A.L.I.C.E Artificial Intelligence Foundation
      • ( )
    • Elizabeth
    • ( )
    • Program-O
    • ( )
  • 13. Prim-bots – examples in SL
    • XD Fusion - Animated Pets, Prim Puppeteer, Shop Assistant ( )
    • [ AA ] Artificial Avatars + Gadgets + Realistic Skins + Free L$ ( )
    • J&M Creations-Scripts, gadgets, fashion, shoes, skins, Furniture (Robotar) ( )
  • 14. Avatar-bot controller programs – examples in SL
    • Thoy’s SLBOT
    • ( )
    • Thoys Bot HQ
    • ( )
    • Pikkubot
    • PikkuBot Shop @ San, meet Eves Sinister
    • ( )
    • SLBOT
      • ( )
  • 15. Chatbots – examples in SL
    • Pandorabot enabled
      • Ana Pandorabot
      • (Restless Photography and Art Gallery)
      • ( )
      • Uncle Irvin
      • (The Curious Prim Main Store, Mythopoeia)
      • ( )
      • Mirna
      • (J&M Creations-Scripts, gadgets, Fashion, shoes, skins, Furniture) ( )
  • 16. Chatbots – examples in SL
    • Other
      • Cyber2 Xue
      • (Artificial Life LAB)
      • ( )
  • 17. Non-player characters
    • A non-player character (NPC) is a character that is controlled by the gamemaster in tabletop role-playing games. When this definition extends to video games, an NPC in a video game is usually part of the program, and not controlled by a human.
      • ( )
    • “ In these virtual worlds, non-player characters use artificial intelligence to take on roles as storytellers, enemies, opponents, partners and facilitators.”
      • (K.E. Merrick, M.L. Maher, Motivated Reinforcement Learning, DOI 10.1007/978-3-540-89187-1_1, © Springer-Verlag Berlin Heidelberg 2009)
  • 18. Meet the Monash Chinese Island NPCs
    • Jingjing Pingping Rongyu (real estate Tianming
    • (waitress) (railway) travel agency) (fruit & veg)
    • Xiaofang Yan Ying
    • (Pharmacist) (Doctor) (Nurse receptionist)
  • 19. Chinese Island NPCs - Architecture
    • Both prim-bot and avatar-bot
    • Standalone bot controller built on Robo2 for Second Life (a wrapper framework of LibOpenMetaverse)
    • AIML and customized a php implementation of the AIML engine – program-O
      • customisation was primarily focused on the Chinese character encoding and decoding and to remove spacing used in the pattern matching mechanism
      • command anchors such as ‘give’, ‘say’ or ‘go to’ are implemented from within AIML and sent to the bot controller
  • 20. Chinese Island NPCs – Other features
    • Are able to process Chinese character input (through modified AIML program) and to produce text-based output in Chinese characters
      • Cannot process English-based input at this stage
    • Dialogue content is tailored to the specific requirements of the inworld lessons, which are inturn based in part on text-book content + real world scenarios
    • All learner dialogue with NPCs is logged for later analysis
  • 21. Chinese Island – the learning environment
    • Chinese Island is a rich Chinese language and culture learning environment in Second Life set up for students and staff at Monash University to engage in both synchronous and asynchronous learning
    • Learning is facilitated and scaffolded by the island’s virtual-physical environment, virtual infrastructure, rich visual environment, rich sound-scape, as well as rich text-based and multi-media learning materials
    • ( )
  • 22. Chinese Island (secondlife://Monash%20University%202/200/170/26)
  • 23. Chinese Island – the lessons
    • Lessons are synchronous
    • Task-based / problem-solving lessons derived from lessons done in main textbook in the classroom
    • Lessons re-enforce textbook content and extend learners by introducing real life scenarios and content in a rich, realistic virtual environment
  • 24. Chinese Island – the lessons & pedagogy
    • All communication text-based
      • Pedagogical goal of re-enforcing pinyin and Chinese character recognition
      • Use classroom language in ‘naturalistic’ manner in ‘semi-spontaneous’ and dynamic situation
    • Task-based / problem-solving lessons create opportunity for ‘meaningful communication’
      • Not just using language for the sake of using it
  • 25. NPCs – classroom management
    • Beginner level students
    • 150 in first semester / 90 second semester
    • SL lessons done in groups of 16 – 18
    • Learners and teaching staff in same computer lab
    • NPCs are capable of conversing with multiple interlocutors simultaneously
      • Human interlocutors cannot possibly cope
    • Through pre-planned dialogue, NPCs can keep the lesson moving without need for teacher involvement
    • Teachers freed to focus on individual learner needs
  • 26. NPCs and lessons – an example
    • Machinima – “Seeing the Doctor”
    • Scenario:
      • Learners buy corn or eggs on street, but become ill (visible symptoms)
      • Go to see doctor in typical university clinic
    • NPCs and roles
      • Tianming – sells corn and tea eggs that cause illness
      • Ying – nurse receptionist (registration and medicine payment)
      • Yan – doctor – diagnose illness and hand out prescription
      • Xiaohong – pharmacist who asks for medication payment receipt and gives out medication
    • URL:
  • 27. NPCs and lessons – an example
    • Machinima – “Seeing the Doctor”
    • NPCs and roles
      • Appear natural within the environment & the scenario
      • When describing any issues with the NPCs, learners often refer to them as ‘he’ or ‘she’
      • NPCs respond to learner queries and greetings in a ‘naturalistic’ and culturally appropriate way ( 您 )
      • NPCs are able to scaffold learners in the process of the task, but always ‘in character’ (“You pay the registration fee by clicking on the metre”, “You can get a medical history at reception”)
  • 28. NPCs and lessons – an example
    • Machinima – “Seeing the Doctor”
    • NPCs and roles
      • NPCs act as gatekeepers during the task
        • “ Have you filled in a medical history card?”
        • “ What is your receipt number for the medical fee?”
      • NPCs are able to provide learners with key artifacts critical to the lesson/task/demonstration of the real world process
        • The medical history
        • The prescription for medicine
        • The medicine
      • NPCs keep the narrative / task moving
  • 29. NPCs - advantages
    • AIML can be tailored
      • The AIML content that forms the basis of the interactive exchanges with learners can be tailored to the specific linguistic goals of the lesson and the level of the learners
    • Bots
      • Are able to handle large numbers of simultaneous conversations, so learners do not have to wait their turn and are not delayed in completing the task within the set time
      • Are consistent with the output (i.e. produce the same structures/vocab, etc., for all learners)
      • Blend in well with the environment and present a ‘human’ face to learners that they can relate to
      • Are always available 24/7 for asynchronous practice
  • 30. NPCs - disadvantages
    • AIML hard to work with
      • Setting up the AIML programs with the requisite content time consuming
      • Because works on key word/phrase/pattern matching basis, hard to predict all the possible variations of learner input
      • Hard to broaden possible scope of conversation
    • Bots
      • Still have limited body language and facial expressions
      • Need to increase the number of command functions activated via AIML dialogue (gestures, opening doors, etc)
      • As resident on an outside server, can suddenly go down in middle of lesson
  • 31. NPCs - disadvantages
    • Voice
      • Currently NPCs are not able to vocalize their output
      • Also not able to recognize verbal input