Rick Hayes-Roth

Decision making in very large networks

Centralized decision making does not work in large federated networks, of which the Internet itself is an example.

The profession of IT Evolutionary system development

Large systems projects are failing at an alarming rate. Its time to take evolutionary design methods off the shelf.

The Value of Truth Telling

Several scholars have suggested that honesty, honor, fairness and other traditional values play a vital role in making capitalism and democracy function (Fukuyama 1995; Zak 2008). Others have recognized that capitalism and democracy reward greed and reinforce antisocial manipulators (Hayes-Roth 2011a). Some believe that enterprises can reconstruct themselves profitably around the principles of integrity and honoring one’s word (Jensen 2011). Our research complements their work by showing how lies materially harm business prospects, making it possible to increase value through truth telling. In the Internet Age, both harmful and salutary information flow at increasing rates, amplifying the latent value of truth (Hayes-Roth 2011c). Promiscuous customers have little loyalty to vendors and shun untrustworthy ones as too risky. The Internet will soon offer improved mechanisms to identify liars and truth-tellers and to filter out untrustworthy messages automatically. Businesses and other organizations will need to seize the opportunities to significantly improve their truthfulness quotients. Quantitative measurements of the value of truth telling will help management steer in a positive direction.

Ready to leap to neo-creationism

Like the master puppet makers of the classic folk tales, artificial intelligence (AI) engineers have built some marvelous machines. The first 50 years of AI focused on programming computers to perform tasks that previously only humans could do tasks such as speech, driving, planning, problem solving and vacuuming. The principal challenges have been to create suitable language systems and inference engines and then to more or less manually stuff those with sufficient facts, heuristics and algorithms to perform well-defined tasks. To get there, we need a singularity of artificial neo-creationism, where we launch artificial beings into the world that can adapt, learn and evolve themselves. The term neo-creationism means an intentional effort to populate the world with intelligent entities initially engineered by humans. The biblical story of Genesis, the heart of creationism, provides an apt foil for understanding the goals and scope of the R&D program advocated here. To reach the goal reasonably quickly, we should equip these creatures with as much capability and knowledge as possible.

A rich semantic model of track as a foundation for sharing beliefs regarding dynamic objects and events

Many defense, homeland security, and commercial security objectives require continuous tracking of mobile entities such as aircraft. The systems that perform these functions produce information products called tracks. A track associates observations with the mobile entity and typically includes position, velocity, and other similar attributes. Military systems have sophisticated tracking and track fusion processes, but lack uniformity in syntactic and semantic content, preventing effective sharing of the information. In other domains of interest, such as seagoing surface ships, dangerous cargo and persons of interest, tracking systems are less mature and have marginal performance. It is now essential that we be able to share information across different tracking systems working in related domains. To combine information from different sources, we need a flexible framework that can tolerate and exploit data products from those systems, even though these systems employ different representations and embody different assumptions. The most basic assumptions concern what the information is intended to mean semantics and how it is intended to be used by a recipient pragmatics. In accordance with best practices in the technology areas of the semantic web and knowledge representation, we seek to reduce the barriers to efficient sharing of information. Our approach is to identify a rich semantic model of tracks that can support multiple important functions: 1 represent a wide variety of meanings and support a broad array of pragmatic goals; 2 reduce the time and cost required to implement capabilities to reason about a new, specialized type of track; 3 simplify the understanding and importation of external sources of track information; 4 help operators describe what attributes of tracks they value in performing their tasks; 5 significantly improve our ability to combine multiple sources of track information; 6 provide a stable and evolvable base for key standards and best practices that support information sharing; and 7 improve bandwidth utilization, raising the proportion of communicated information that recipients consider significant, by delivering valued information at the right time VIRT. This paper describes the proposed rich semantic track model and ongoing efforts to share it widely with appropriate communities of interest.