To solve complex, real-world problems, AI systems often must integrate component technologies, such as planning, reasoning, language, dialogue, perception, goal-driven action, and learning. Prototypical examples of such integrated systems include software agents, autonomous robots, robots that interact with humans, intelligent tutoring systems, and virtual characters. The Integrated Intelligence track welcomes submissions on issues that arise in the design and construction of such systems, and with clear evidence for the efficacy of the integrated system.
Papers submitted to this track highlight synergistic effects of integrating components from distinct areas of AI to achieve intelligent behavior. They articulate the innovative mechanisms used to combine multiple components and should demonstrate the synergy achieved through this integration. Topics may range from small-scale integrations of two components to large-scale efforts that support robust autonomous agents.
Relevant topics include the following:
- Autonomous robot systems
- Robots that interact with humans
- Autonomous software agents
- Cognitive architectures
- Intelligent tutoring systems
- Intelligent user interfaces
- Multimodal communication
- Multisensory fusion
- Robot architectures
- Virtual characters
Papers that include clear claims about the benefits of integration and supporting evidence received preference. Acceptable forms of evidence include theoretical analyses, experimental evaluation, matches to human behavior, and demonstrations of new functionality, provided they examine the synergistic effects of integrating two or more component abilities.
Special Track Cochairs
Pat Langley (Arizona State University)
Alan Schultz (Naval Research Laboratory)