More AGI Goodies
http://people.csail.mit.edu/kersting/plmr/
The above website has a list of AI systems, all created with the goal of integrating logic and probability theory. This goal is more interesting than it sounds at first. There are trivial integrations of logic and probability theory (such as using logic to reason about probability) and there are non-trivial integrations. Nontrivial integrations are of great interest, because they allow algorithms from both arenas to be applied, they allow easy "softening" of existing hard-logic knowledge bases that prove to be too inflexible (amazingly, Cyc has started taking that strategy), and they open up new possibilities for learning and inference. All of the above systems are openly available (which is amazing!).
Of particular interest is Alchemy. Alchemy has a deceivingly simple-sounding and intuitive scheme: take a set of logical statements and attach a weight to each, representing how much the system should endorse each claim. The weights don't just range between 0 and 1 like probabilities, they can be as large as you like (infinity would mean absolutely true). Together, all of the propositions and there weights are transformed by the system onto a standard type of probabilistic model (a markov random process), which can be reasoned about using well-established algorithms. However, the group also has invented some amazing-sounding algorithms of their own...
Wednesday, April 16, 2008
Friday, April 11, 2008
This is old news now, but the First Annual AGI Conference occurred recently. This is fairly exciting in and of itself, but more exciting is that all the papers are available free online. This provides a very interesting snapshot of what the emerging "AGI Community" is and will be about.
For those who don't know, AGI is a term created to distinguish general AI (aiming at human-level intelligence in a broad range of tasks) from narrow AI (which aims for high performance on some single, specialized task). Typical narrow-AI applications include chess playing programs, stock-market forecasters, face recognition software, and generally anything else AI is used for these days. A typical example of AGI (standing for artificial general intelligence) might be a project aiming to make a "baby machine" (an AI that is good at nothing, but could be trained to do anything).
http://www.agiri.org/wiki/index.php?title=Artificial_General_Intelligence
For those who don't know, AGI is a term created to distinguish general AI (aiming at human-level intelligence in a broad range of tasks) from narrow AI (which aims for high performance on some single, specialized task). Typical narrow-AI applications include chess playing programs, stock-market forecasters, face recognition software, and generally anything else AI is used for these days. A typical example of AGI (standing for artificial general intelligence) might be a project aiming to make a "baby machine" (an AI that is good at nothing, but could be trained to do anything).
http://www.agiri.org/wiki/index.php?title=Artificial_General_Intelligence
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