Tradeoffs in the inductive inference of nearly minimal size programs

Inductive inference machines are algorithmic devices which attempt to synthesize (in the limit) programs for a function while they examine more and more of the graph of the function. There are many possible criteria of success. We study the inference of nearly minimal size programs. Our principal results imply that nearly minimal size programs can be inferred (in the limit) without loss of inferring power provided we are willing to tolerate a finite, but not uniformly, bounded, number of anomalies in the synthesized programs. On the other hand, there is a severe reduction of inferring power in inferring nearly minimal size programs if the maximum number of anomalies allowed is any uniform constant. We obtain a general characterization for the classes of recursive functions which can be synthesized by inferring nearly minimal size programs with anomalies. We also obtain similar results for Popperian inductive inference machines. The exact tradeoffs between mind change bounds on inductive inference machines and anomalies in synthesized programs are obtained. The techniques of recursive function theory including the recursion theorem are employed

One-Sided Error Probabalistic Inductive Interface and Reliable Frequency Identification

For EX- and BC-type identification, one-sided error probabilistic inference and reliable frequency identification on sets of functions are introduced. In particular, we relate the one to the other and characterize one-sided error probabilistic inference to exactly coincide with reliable frequency identification, on any setM. Moreover, we show that reliable EX and BC-frequency inference forms a new discrete hierarchy having the breakpoints 1, l/2, l/3, ..

One-Sided Error Probabalistic Inductive Interface and Reliable Frequency Identification

For EX- and BC-type identification, one-sided error probabilistic inference and reliable frequency identification on sets of functions are introduced. In particular, we relate the one to the other and characterize one-sided error probabilistic inference to exactly coincide with reliable frequency identification, on any setM. Moreover, we show that reliable EX and BC-frequency inference forms a new discrete hierarchy having the breakpoints 1, l/2, l/3, ..

Intelligent failure-tolerant control

An overview of failure-tolerant control is presented, beginning with robust control, progressing through parallel and analytical redundancy, and ending with rule-based systems and artificial neural networks. By design or implementation, failure-tolerant control systems are 'intelligent' systems. All failure-tolerant systems require some degrees of robustness to protect against catastrophic failure; failure tolerance often can be improved by adaptivity in decision-making and control, as well as by redundancy in measurement and actuation. Reliability, maintainability, and survivability can be enhanced by failure tolerance, although each objective poses different goals for control system design. Artificial intelligence concepts are helpful for integrating and codifying failure-tolerant control systems, not as alternatives but as adjuncts to conventional design methods

MANPOWER IN THE DEVELOPMENT OF THE COAST GUARD NATIONAL SECURITY CUTTER: A HUMAN SYSTEMS INTEGRATION CASE STUDY

The National Security Cutter (NSC) is the U.S. Coast Guard’s (USCG) largest acquisition program to date. Despite the NSC’s significance, its acquisition (2002–present) has suffered numerous performance and cost-related setbacks ostensibly linked to Human System Integration (HSI) issues. In this thesis, we provide a historical HSI case study of the NSC program focusing on manpower, highlighting critical gaps in early concept analyses. While current USCG policy provides definitive guidance on HSI’s inclusion in acquisition programs, little evidence exists linking HSI-related decisions to specific system performance and life-cycle cost outcomes. We use process tracing to systematically establish linkages between USCG HSI policy, NSC program decisions, and specific system performance and life-cycle cost outcomes, illustrating the importance of HSI’s inclusion early in the acquisition life cycle. We produce a template for analyzing HSI decisions and outcomes in large-scale acquisition programs and provide a model for future systems engineering case studies. Our research will guide future program managers and HSI researchers in program management planning endeavors. Finally, our recommendations include the reinforcement of early and iterative HSI tradeoff considerations, organization and program-level integration of HSI in major program integrated product teams, strict adherence to USCG policy-defined HSI-related activities, and purposeful HSI case study taxonomy.Lieutenant Commander, United States Coast GuardApproved for public release. Distribution is unlimited

An optimal repartitioning decision policy

A central problem to parallel processing is the determination of an effective partitioning of workload to processors. The effectiveness of any given partition is dependent on the stochastic nature of the workload. The problem of determining when and if the stochastic behavior of the workload has changed enough to warrant the calculation of a new partition is treated. The problem is modeled as a Markov decision process, and an optimal decision policy is derived. Quantification of this policy is usually intractable. A heuristic policy which performs nearly optimally is investigated empirically. The results suggest that the detection of change is the predominant issue in this problem

Machine learning : techniques and foundations

The field of machine learning studies computational methods for acquiring new knowledge, new skills, and new ways to organize existing knowledge. In this paper we present some of the basic techniques and principles that underlie AI research on learning, including methods for learning from examples, learning in problem solving, learning by analogy, grammar acquisition, and machine discovery. In each case, we illustrate the techniques with paradigmatic examples

The Presumption against Expensive Health Care Consumption

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