1. Clairvoyant machine CM: why? Test-bed for many technologies developed in our School. CM project T-T-S synthesis speech recognition Talking heads Coordination Graphics Cognitive Robotics Cognitive science AI Mind-bots Lingu-bots Knowledge modeling Info-retrieval VR avatars Robotics

2. CM machine: what? What should it be? talking head with TTS + speech recognition; lingu-bot able to have some dialog; first simulation than robot; not too ambitious at the beginning, with potential for growth 20 questions game20 questions game – non-trivial if not restricted to animals/minerals or plants, may start from simple domains. Other games of this sort? Trivia games? Reading books?Trivia gamesReading books PC assistant? UltraHal is on the market. MIT Start systemMIT Start system, web-based question answering system. Perhaps best for science?

3. CM: how? Quick and dirty: put together ready-made components for Cyberworlds in 2 weeks, for Science Museum for Christmas? V1: Haptek virtual friend + speech recognition + play 20Q over the Internet ?Haptek virtual friend Feed text scripts to Haptek, work out scripts that correlate words with emotions and head movements. Requires: javascript + VB programming Challenge: integration of different techniques. Haptek + speech recognition may be commercial. Game may be on the Internet, responses are read loud and entered via speech.

4. CM: evolution. Add more games, answers to questions about science, geography, movies etc (filtering MIT Start information). Add your own elements: heads + graphics + lips synchro + speech synthesis etc, whenever we can improve CM. Put it on robot, add camera, recognition of face/sex, ex. say ‘Hallo pretty girl”, or ‘Hello Wlodek’ etc. Add bot to talk about NTU, museum, or other specialized subject: lingubots from Kiwi logic? Add your own 20-Q game, there are many realizations, theories of semantic memory may be tested this way. Michalski had a machine learning system discovering rules from examples, touring eight U.S. Museums of Science.machine learning system

5. CM: AI + cognitive aspects Development of mind-bots: bots are stupid, do not reason, have problems with understanding simple sentences. Use ontologies + OpenCyC NL to understand more. Mindbots: based on more sophisticated model of mind. Use SOAR-NL, for problem solving, language & learning. Use ACT-R to model user’s mind, good for tutorials.good for tutorials Developmental approach: Ai baby mindAi baby mind Alan and Hal ? In a robot?

6. ??? Links to bots and more are at: http://www.ntu.edu.sg/home/aswduch/ai-ml.html#Agent These notes: http://www.ntu.edu.sg/home/aswduch/ref/CM1.ppt