Achieving Human-Level Intelligence through Integrated Systems and Research: Papers from the AAAI Fall Symposium
Nicholas Cassimatis and Patrick Winston, Cochairs
Although there has been substantial progress in some of the subfields of artificial intelligence during the past three decades, the field overall is moving toward increasing subfield isolation and increasing attention to near-term applications, retarding progress toward comprehensive theories and deep scientific understanding, and ultimately, retarding progress toward developing the science needed for higher-impact applications. Recent work in artificial intelligence, in addition to cognitive psychology, neuroscience, and linguistics, presents an opportunity to reverse this specialization and reinvigorate the field's focus on understanding and developing human-level intelligence. Because there are so few venues for research on integration and because the opportunity is so great, this symposium gathered researchers working across the boundaries of their subfields to explore new computational techniques and research methodologies for integrating research results to produce more intelligent systems. The symposium addressed three broad topics of interest. First, what can models of vision, language, learning, and reasoning in fields such as cognitive psychology, linguistics, and neuroscience contribute to artificial intelligence? Is there a way to describe and organize these results so that they can be more easily shared and combined across subfields? Second, how can we integrate multiple perception, action, representation, learning, planning, and reasoning systems to build cognitive models and intelligent systems that significantly advance the level of intelligence we can model or achieve? Is there a way to characterize the strengths and weaknesses of each approach and determine when to use each? Finally, what kind of theoretical, methodological, or technological innovations are needed to accelerate this research? Will it require advances in cognitive modeling, cross-domain and intersubfield ontologies, or some kind of institutional transformation?