With comments from OntologyStream

The DARPA Information Processing Technology Office (IPTO) solicits innovative proposals for a new program on Real-World Reasoning. A principal mission of IPTO, launched at DARPA in 2002, is to create the technologies critical to building practical cognitive information processing systems. Developing innovative machine reasoning technology that can effectively deal with the real world is central to this mission [1: Comment from Prueitt] .

The objective of the REAL-WORLD REASONING (REAL) program is to explore and develop foundations, technology, and tools to enable effective, practical automated reasoning of the scale and complexity required for computers to perform complex tasks in the real world requiring intelligence. Effective, ?real-world? machine reasoning requires inference in environments that are far more complex in scale and scope than those tackled by current machine reasoning methods [2: Comment on independence of infrastructure]

Enduring real-world systems need to deal with vast amounts of knowledge and information, often concerning dynamic and intentional phenomena. In addition, beliefs about the environment are often uncertain and involve plausible but not provable assumptions. The REAL program solicits innovative research efforts that can make fundamental and breakthrough advances in real-world reasoning to deal with these and related problems. Research efforts must implement the algorithms and technology in specific testbeds, and demonstrate novel capabilities for real-world reasoning.

Specifically, the program intends to: 1. Develop and demonstrate innovative techniques that push the envelope of performance of reasoning engines, in terms of the scale of the problems that can be dealt with, and the speed and correctness of reasoning. 2. Explore, develop, and demonstrate novel methods that extend the breadth of reasoning to deal with a.

Uncertain and dynamic environments where the knowledge base is characterized by uncertain and temporally changing information; and, b. Strategic environments characterized by goals and intentions of many interacting agents and actors, in both cooperative and non-cooperative contexts. 3.Build and demonstrate embedded reasoners for active knowledge bases that recognize the commonalities and similarities among multiple ontologies, and combine and merge them, so as to enable well-informed reasoning through the exploitation of all information in the knowledge base.