www.greatmindsworking.com

2005 IEEE/WIC/ACM International Joint Conference on Web Intelligence (WI'05)

September 19-22, 2005
Compiegne University of Technology, France

http://www.comp.hkbu.edu.hk/WI05/
http://www.hds.utc.fr/WI05/

Sponsored By:
IEEE Computer Society
Web Intelligence Consortium (WIC)
Association for Computing Machinery (ACM)

The Call for Papers for CoNLL-2005: Ninth Conference on Computational Natural Language Learning organized at ACL 2005, Ann Arbor, MI from June 29-30, 2005 is now online here.

The prospect of metaprogramming tools raises threats and opportunities for OSS. The biggest threat is that they could be used (legally or not) to strip copyright from OSS. On the plus side, innovation in the next version of the GPL could solve the patent morass by adding a "patent shredder" to "copyleft". I propose the introduction of a "Greater GPL" in GPL Version 3 to address these issues.

http://www.pagesmiths.com/category-ip.html

Jim White

Dear Patrons,

Will you consider visiting my website and reading a book I've written- "How to Design a Universal Artificial Intelligence." For over ten years, I have been working on a method of semantic interpretation that applies in any situation. Using this method, I believe that a software program can pass the Turing Test. The book is currently online, in its entirety, and I am requesting your review of this work. This is it; this is real; this is a working counterpart program.

I currently have the entire book online, in html, for anyone to read (and a paperback is available for purchase). I can promise you that this is not an amateurish attempt to make a counterpart machine. This is an approach is based upon a method of semantic interpretation that is fail-safe. In adult form, this machine will recognize and analyze all human actions, all discrete human actions, without fail. This is a program that can break down human conversation into its elemental parts and elemental motives. This is a very different approach than that of others studying human cognition.

I would hope that you understand that I am quite knowledgeable in my profession of construction and that I have inadvertently studied human behavior from a very different perspective. I am not a psychologist, a biologist, a mathematician, or even a programmer. I am a behaviorist. And like other behavioral psychologist I am only analyzing what is tangible, calculable. My research is based upon empirical data.

I thank You for your time, and I hope that you will consider this approach to the Turing problem.

Wil Holland

My website
My email

Slashdot has discussion of this Language Learning & Technology article which discusses modifiying the popular game The Sims for educational purposes, more specifically, teaching a foreign language.

KurzweilAI had a line to this Guardian Unlimited article discussing Bruce Lahn's research on the sophistication of the human brain.

From the article, "Professor Lahn's research, published this week in the journal Cell, suggests that humans evolved their cognitive abilities not owing to a few sporadic and accidental genetic mutations - as is the usual way with traits in living things - but rather from an enormous number of mutations in a short period of time, acquired though an intense selection process favouring complex cognitive abilities."

The First Symposium on Semantic Mining in Biomedicine (SMBM 2005) will be held from April 10 - 13, 2005. It is being hosted by the European Bioinformatics Institute (EBI) in Hinxton, Cambridge, UK.

More information is available here.

A workshop on the Analysis of Informal and Formal Information Exchange during Negotiations will be held from May 26-27, 2005 at the University of Ottawa in Ottawa, Ontario, Canada.

More information is available here.

The AAAI-05 Workshop on Question Answering in Restricted Domains will be held on July 9 or 10, 2005 (date TBA) in Pittsburgh, Pennsylvania as part of AAAI-05.

More information is available here.

This research focuses o­n the development of a telerobotic system that employs several state-action policies to carry out a task using o­n-line learning with human operator (HO) intervention through a virtual reality (VR) interface. The case-study task is to empty the contents of an unknown bag for subsequent scrutiny.A system state is defined as a condition that exists in the system for a significant period of time and consists of the following sub-states: 1) the bag which includes a feature set such as its type (e.g., plastic bag, briefcase, backpack, or suitcase); 2) the robot (e.g., gripper spatial coordinates, home position, idle, performing a task) and 3) other objects (e.g., contents that fell out of the bag, obstructions).A system action takes the system to a new state. Action examples include initial grasping point, lift and shake trajectory, re-arranging the position of a bag to prepare it for better grasping and enable the system to verify if all the bag contents have been extracted.Given the system state and a set of actions, a policy is a set of state-action pairs to perform a robotic task. The system starts with knowledge of the individual operators of the robot arm, such as opening and closing the gripper, but neither it has policy for deciding when these operators are appropriate, nor does it have knowledge about the special properties of the bags. A policy is defined as the best action for a given state. The system learns this policy from experience and human guidance and is found to be beneficial if a bag was grabbed successfully and all its contents have been extracted.The expected contributions of this research include the system ability to accept or reject HO new policies (e.g., add or remove possible grasping points, lifting, and shaking trajectories) through a VR interface when it encounters a situation it cannot handle or its learning rate is considered to be low. Policy examples are to let the HO classify the type of a bag (e.g., a briefcase) when it was recognized mistakenly as a different type (e.g., a suitcase) and to provide a set of possible grasping points by the HO when the system finds it difficult to recognize points that are beneficial for completing the task. When HO intervention is found to be beneficial, the system learns, and its dependence o­n the HO decreases.Learning the optimal policy for bag classification will be conducted using support vector machines (SVMs). The inference of the SVMs will be a recommendation for a set of possible grasping points. Reinforcement learning (e.g., Q-learning) will be used to find the best action (e.g., determining the optimal grasping point followed by a lift and shake trajectory) for a given state.For testing the above, an advanced virtual reality (VR) telerobotic bag shaking system is proposed. It is assumed that several kinds of bags are placed o­n a platform. All locks have been removed and latches and zippers opened. The task of the system is to empty the contents of an unknown bag o­nto the platform for subsequent scrutiny. It is assumed that the bag has already passed X-ray inspection to ensure the bag is not empty and does not contain obvious explosives (e.g., mines, gun bullets).Keywords: support vector machines, robot learning, machine vision, virtual reality, human-robot collaboration, telerobotics