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Submitted by ai on Wed, 2009-06-03 00:11
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In this post I'll try to figure out (primarily for myself) what is Artificial Intelligence.
Evidently, the "artificial" part requires no explanation, and the real problem is only with the "intelligence" part.
An extremely over-simplified, and actually incorrect definition would be "Intelligence is the ability to think logically". Evidently, logic cannot be the sole basis of intelligence, at least because intelligence requires an ability to comprehend the environment, not only deduct. Moreover, logic itself is not an ultimate intelligence resource - it cannot explain the environment. Even planning an experiment - a generic method of studying the environment - requires not only logic, but also some kind of stimulus to learn the environment (possibly derived from the adaptation requirement which, in turn, is one of the mechanisms of self-preservation and self-defense).
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Submitted by ai on Sun, 2009-05-31 09:58
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In this post, some definitions and examples are given. This is an introductory text.
First of all there is a need to explain why "intelligent" is in braces in the title. Well, it's simple: whatever the agents are at the moment of writing, they are just specific, narrow algorithms with no signs of intelligence. As soon as I come across the evidence of the contrary, I will happily remove the braces around "intelligent". But for now - braces stay.
What is an agent? According to the numerous sources I checked, agent is an entity with some characteristic features. These fundamental features are:
- agent acts on behalf of others. For example, you may hire a person who would attend parents' meetings at the school of your children: in this case, that would be a "parental agent" :) , who comes to the meetings on your behalf.
- agents are to some extent autonomous (i.e., enjoy some degree of autonomy). In our example, the "parental agent" has freedom to act and respond the way he feels appropriate in his communication with other parents at the meeting; but at the same time he must follow the behaviour strategy you outlined for the official messages announced by the school staff.
- agents are proactive and reactive. Proactive means that agent may exhibit his own independent initiative, which is not (at least directly) related to the delegated tasks of the agent. Reactive tells us that agents will respond to stimuli - e.g., given a task, agent will try to do that task.
- agents are able to learn - that is, they have memory, which influences their further actions.
- agents may be cooperative - help each other or just join efforts to complete given tasks.
- agents are mobile.
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Carnegie Mellon University Open Source Toolkit For Speech Recognition
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Open-Source Large Vocabulary CSR Engine Julius
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Founded in November 1992. UAsIPPR is a member of IAPR - International Association for Pattern Recognition.
The Ukrainian Association for Information Processing and Pattern Recognition is a voluntary public creative scientific organization which unites research teams of institutions, organizations as well as citizens of Ukraine on a voluntary basis and a community of interests to achieve the goal and tasks provided by the UAsIPPR Constitution.
Now UAsIPPR unites more than 75 researchers. It organizes international conferences, publishes their proceedings.
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The Dallas Personal Robotics Group (DPRG), founded in June of 1984, is one of the US oldest special interest groups dedicated to the development and use of personal robotics. The DPRG is a 501(c)(3) not for profit educational organization. DPRG members are interested in autonomous robots, movie replica robots, vintage robots, robot and kinetic art, as well as just about anything involving electronics, technology, or science.
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An Executive is responsible for task execution on-board an autonomous robot. TREX is a hybrid executive combining goal-driven and event-driven behavior in a unified framework based on temporal plans and temporal planning. TREX uses a single declarative programming language and shared runtime state for both deliberation and execution offering a seamless integration between planning and control. TREX also provides explicit support for compositional control which improves modularity, scalability, and robustness.
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Science and semi-technical jobs in sciences. Updated daily. Doesn't appear to have any AI-related jobs, but I might have missed those.
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Free Software tools for robot and sensor applications.
The Player Project creates Free Software that enables research in robot and sensor systems. The Player robot server is probably the most widely used robot control interface in the world. Its simulation backends, Stage and Gazebo, are also very widely used.
Released under the GNU General Public License, all code from the Player/Stage project is free to use, distribute and modify. Player is developed by an international team of robotics researchers and used at labs around the world.
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OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real time computer vision.
Example applications of the OpenCV library are Human-Computer Interaction (HCI); Object Identification, Segmentation and Recognition; Face Recognition; Gesture Recognition; Motion Tracking, Ego Motion, Motion Understanding; Structure From Motion (SFM); Stereo and Multi-Camera Calibration and Depth Computation; Mobile Robotics.
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Open-source, BSD-licensed robotics software libraries and platform (ROS).
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(Note: self-signed SSL certificate is used, don't be surprised with a warning.)
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Shakey is a nickname of a robot.
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Theory and applications of intelligent systems.
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The Artificial Intelligence and Education (AI-ED) Group is part of the Division of Informatics of the University of Edinburgh, although it has strong links with other research groups and institutes within and outwith Edinburgh. The group's main purpose is the application of Artificial Intelligence techniques and methods to support learning and teaching/training.
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