artificial general intelligence

Report on the First Conference on Artificial General Intelligence (AGI-08)

AI Magazine

The First Conference on Artificial General Intelligence (AGI-08) was held on March 1-3, 2008, at the University of Memphis. The overall goal of the conference was to work toward a common understanding of the most promising paths toward creating AI systems with general intelligence at the human level and beyond, and to share interim results and ideas achieved by researchers actively working toward powerful artificial general intelligence.

Mixing Cognitive Science Concepts with Computer Science Algorithms and Data Structures: An Integrative Approach to Strong AI

AAAI Conferences

We posit that, given the current state of development of cognitive science, the greatest synergies between this field and artificial intelligence arise when one adopts a high level of abstraction. On the one hand, we suggest, cognitive science embodies some interesting, potentially general principles regarding cognition under limited resources, and AI systems that violate these principles should be treated with skepticism. But on the other hand, attempts to precisely emulate human cognition in silicon are hampered by both their ineffectiveness at exploiting the power of digital computers, and the current paucity of algorithm-level knowledge as to how human cognition takes place. We advocate a focus on artificial general intelligence design. This means building systems capturing the salient high-level features of human intelligence (e.g., goal-oriented behavior, sophisticated learning, self-reflection, etc...), yet with software architectures and algorithms specifically designed for effective performance on modern computing hardware. We give several illustrations of this broad principle drawn from our work, including the adaptation of estimation of distribution algorithms in evolutionary programming for complex procedure learning.