Published on

Published in: Technology
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide
  • The Singularity represents an "event horizon" in the predictability of human technological development past which present models of the future may cease to give reliable answers, following the creation of strong AI or the enhancement of human intelligence.The Singularity is the technological creation of smarter-than-human intelligence. There are several technologies that are often mentioned as heading in this direction. The most commonly mentioned is probably Artificial Intelligence, but there are others: direct brain-computer interfaces, biological augmentation of the brain, genetic engineering, ultra-high-resolution scans of the brain followed by computer emulation. Some of these technologies seem likely to arrive much earlier than the others, but there are nonetheless several independent technologies all heading in the direction of the Singularity – several different technologies which, if they reached a threshold level of sophistication, would enable the creation of smarter-than-human intelligence.
  • Cognitive Architecture (overall design of the AGI, different parts and how they interacts with each others). Modular approach.Knowledge Representation (how the system store different type of knowledge such a as declarative, procedural or episodic and how it creates its own). Atome table with connectionist and symbolic systemsLearning (how does it learn new type knowledge and how it learn to learn). MOSES and PLN algoTeaching Methodology (how with coupled with other systems it gain knowledge about itself and others). AGISim integrationAGI cognitive science flow chart
  • Web based virtual worlds:, habbo.comSocial Network: myspace, facebook.beboStand alone: Total Active Subscriptions for October 2007 for over 100 tracked MMO Games, including WoW, EVE, SL, There
  • WebFlock 1.0. WebFlock is an application for private-labeled, Web-based virtual experiences. It provides a visually immersive environment for social interaction, media consumption and game play
  • In a typical real-life version of this test, a child witnesses a series of events in which Person A places an object (such as a teddy bear) in a certain location (such as a cabinet). Person A then leaves the room, and during his absence Person B moves the object to a new location (such as the refrigerator). The child is then asked to predict where Person A will look for the object when he gets back.The right answer, of course, is the cabinet, but children age 4 and under will generally say the refrigerator because they haven’t yet formed a theory of the mind of others. The researchers recreated the same situation in Second Life, using an automated theorem prover coupled with procedures for converting conversational English in Second Life into formal logic, the native language of the prover. When the code is executed, the software simulates keystrokes in Second Life. This enables control of “Eddie,” who demonstrates an incorrect prediction of where Person A will look for the teddy bear — a response consistent with that of a 4-year old child.  But, in an instant, Eddie’s mind can be improved, and if the test is run again, he makes the correct prediction.
  • Is the online Environment suited to Kinesthetic learners?How do we make online environment more inviting & Supporting of kinesthetic learners?Transition From 2D/3D graphical interactive interface to 3D on-line communities
  • David Kolb’s ModelLearning Style InventoryAnthony Gregorc’s ModelFleming’s VARK ModelLearning Style TestJackson’s Neuropsychological ModelLearning Styles Profiler
  • mesca

    1. 1. Virtual Environments Meet Artificial Intelligence <br />July 2009<br />Xavier Laurent<br />University of Bangor<br />
    2. 2. Research Focus<br />
    3. 3. What is it about?<br />
    4. 4. The Singularity<br />Ray Kurzweil<br />Inventor and Futurist<br />
    5. 5. Other Views on the Singularity<br />Dr. Peter Norvig<br />Google Director of Research<br />
    6. 6. Emulating Intelligence via brain scanning<br />Blue brain project<br />(bottom-up or reverse engineering)<br />An entire neocortical column lights up with electrical activity. Modeled on a two-week-old rodent brain, this 0.5 mm by 2 mm slice is the basic computational unit of the brain and contains about 10,000 neurons. This microcircuit is repeated millions of times across the rat cortex and many times more in the brain of a human. Courtesy of Alain Herzog/EPFL<br />
    7. 7. What is it about?<br />
    8. 8. Artificial General Intelligence and its Potential Role in the Singularity<br />Narrow AI<br />Artificial Intelligence (AI), Artificial General Intelligence (AGI) or Strong AI or Human Level Intelligence<br />Holy Grail of AI: creating machinesthat have similar minds to ours.<br />
    9. 9. Unpopularity of AGI<br /><ul><li>AI winter which promises that could not be kept
    10. 10. Penrose / Hameroff, Intelligence is based on human consciousness which is in turn based on quantum gravity based dynamics operating within brain dynamics (1997, 2002)
    11. 11. Beyond Technology capabilities
    12. 12. Emulating AGI via brain scanning (Kurzweil, 2005)
    13. 13. No immediate results compared to Narrow AI
    14. 14. General purpose systems are not as good as special purpose ones
    15. 15. AGI is dangerous ethical issues
    16. 16. Scaling up of cognitive architectures</li></li></ul><li>Different approaches to AGI<br />
    17. 17. Novamente <br />
    18. 18. Definition of Intelligence<br />It is the ability to achieve complex goal in complex environment.<br />Autonomy<br />Understanding of self and others<br />Understanding of what is the problem<br />Ben Goertzel<br />
    19. 19. Novamente Hybrid Approach <br />
    20. 20. What is it about?<br />
    21. 21. Human Cognitive Development<br />
    22. 22. Sensorimotor Stage<br />Circular reaction, object permanence, goal directed behavior, A not B search error<br />Knowledge that objects exist, independent of our perception of them <br />Piaget suggests that until 18 months of age appearances and disappearance of an object are not taken as the same object. <br />Out of sight, out of mind<br />
    23. 23. The Object Permanence<br />
    24. 24. AGI Education<br />
    25. 25. What is it about?<br />
    26. 26. Virtual Worlds<br />Technology Evaluation for Marketing and Entertainment Virtual worlds, July 2008<br />
    27. 27. Virtual Worlds Road Map<br />
    28. 28. What is it about?<br />
    29. 29. Embodiment and AI<br />The natural synergy between advanced AI and gaming/virtual worlds has been avidly discussed for at least a decade, see (john E.laird 2000)<br /><ul><li>Some AI theorists believe that robotic embodiment is necessary for the achievement of powerful AGI (Rodney Brooks for instance is a prominent champion of this perspective)
    30. 30. Others believe embodiment is entirely unnecessary, and one can create a human-level AGI exclusively using other mechanisms, e.g. textual conversation, interaction in formal logic, etc.
    31. 31. Novamente believes that embodiment is extremely convenient for AGI though perhaps not strictly necessary; and that virtual-world embodiment is an important, pragmatic and scalable approach to pursue alongside physical-robot embodiment. </li></li></ul><li>Why simulated worlds?<br />Cheaper than robotics<br />Controllability of the environment with physics<br />Masses of potential AGI teachers (like Wikipedia or Google implicit knowledge)<br />Linguistic and embodied perceptual/active experiences (different from chat robots)<br />Different form of avatars (Virtual animals, shopkeepers etc)<br />Commercial vehicle for the popularization and monetization of early-stage AGI’s<br />It&apos;s easier for a distributed team to work on project <br />
    32. 32. Virtual Environment Problems<br />SL does not lend itself well with detailed perceptual and motoric interaction. It is better for its users base. Integration of virtual world platforms with robotics simulation platforms such as Player/Gazebo would be one route.<br />SL Lack of integrity with other tools<br />Virtual worlds needs better richness of physics and sensory motions(What must a world be, that an intelligent system may grow and learn within it?)<br />Object recognition and integration into learning. At present time objects are labeled with metadata indicating their type<br />
    33. 33. Example solution: Integration of a robot simulator with a virtual world engine<br />+<br />Player / Gazebo: 3D robot control + simulation framework<br />RealXTend/OpenSim: open-source virtual world<br />It seems feasible to replace OpenSim’s physics engine with appropriate components of Player/Gazebo, and make coordinated OpenSim client modifications<br />
    34. 34. Work done in simulated worlds<br />Object permanence / Object recognition in AGISIM<br />False belief test in Second Life<br />Current SL stage with Novamente cognition engine, virtual pet (fetch game)<br />
    35. 35. Novamente AI Sim<br />Hiding an object and seeing if the AI remembers that it still exists (what Piaget called object permanence)<br />
    36. 36. Fetch games<br />Using imitation-reinforcement-correction methodology to teach avatars various behaviors (verbal and non verbal communication)<br />
    37. 37. Leonardo, the creation of MIT scientists<br />Passed the test of false Belief<br />
    38. 38. What is OpenCog<br />The Open Cognition Framework (OpenCog) provides research scientists and software developers with a common platform to build and share artificial intelligence programs. <br /><br />
    39. 39. What do they offer to Kinesthetic learners and how can they be improved in the future. How virtual worlds can help to develop Intelligence for Human and Artificial Agents?<br />Learning style in Virtual Worlds<br />
    40. 40. Road Map<br />Look at the different type of learning and choose kinesthetic learning style<br />Fleming and Mills’ Vark model for kinesthetic learners<br />Virtual worlds vs. other 3D environments, why a Second Life type environment should bring something to kinesthetic learners?<br />What Virtual Worlds could bring to kinesthetic learners?<br />What else could be done to improve kinesthetic learning in a virtual world? <br />
    41. 41. Fleming&apos;s VARK model <br /> visual learners<br /> auditory learners<br /> reading/writing-preference learners<br /> kinesthetic learners or tactile learners<br />Kinesthetic learning is when someone learns things from doing or being part of them. They make up about 15% of the population and struggle to pick things up by reading/ listening to things<br />
    42. 42. Naïve Physics<br />Naive physics (Hayes, 1985) refers to the theories about the physical world that human beings implicitly develop and utilize during their lives.<br />What goes up must come down.<br />A dropped object falls straight down.<br />A vacuum sucks things towards it.<br />Centrifugal force throws rotating things outwards.<br />An object is either at rest or moving, in an absolute sense.<br />
    43. 43. Current Virtual Worlds lack fluids, powders, pastes, fabrics … they don’t completely implement “naïve physics”<br />
    44. 44. One likely solution: bead physics<br />Spherical beads with specially designed adhesion properties can emulate fluids, fabrics, pastes, strings, rubber bands, etc.<br />Bead physics can be added to virtual world physics engines<br />
    45. 45. What Must a World Be That an AGI Can Develop In It?<br />
    46. 46. Ethical views: Friendly AI<br />Goal Invariance Under Radical Self-Modification<br /> How to architect an AGI system so as to maximize the odds that, as it radically self-modifies and self-improves, it will not lose track of its originally programmed/taught goal system? <br />Eliezer Yudkowsky<br />
    47. 47. A Matrioshka brain<br />