201885623
Manufacturing supply chain applications: modeling computer assembly operations for supply chain integration
Factory operations have been modeled for years to understand the relationship between the different design and policy factors and the performance measures of interest. The increasing awareness of the need to manage factories as a link in the supply chain places a corresponding requirement for an enhanced approach for factory modeling. This paper describes the modeling of a computer assembly factory for supply chain integration by including aspects of inbound and outbound logistics and relevant business processes. Lessons are drawn based on the experience.
6477912
Stress testing a supply chain using simulation
Simulation provides the capability to evaluate performance of a system operating under current or proposed configurations, policies and procedures. It is very applicable to evaluation of strategic and operational level plans for supply chains. It is especially useful for exploring the viability of a supply chain before beginning production. This paper describes the use of simulation for determining the readiness of a supply chain designed by a small company for providing sub-systems to a defense contractor. The supply chain had to be stress tested at surge and mobilization volume levels to meet the requirements. Simulation provided the ideal methodology to identify and demonstrate the behavior of the supply chain under stress and evaluate strategies to meet the defined volumes. It was used to prove the readiness of the supply chain reducing perceived risks in using the virtual operation.
7115385
Integrated simulation and gaming architecture for incident management training
The simulation-based training systems that are available or under development today for incident management are typically focused on macro level sequence of events. A few systems targeted at individual responders are under development using a gaming environment. Separate uses of such systems provide disparate experiences to decision makers and individual responders. There is a need to provide common training experiences to these groups for better effectiveness. This paper presents a novel approach integrating gaming and simulation systems for training of decision makers and responders on the same scenarios preparing them to work together as a team. An integrated systems architecture is proposed for this purpose. Major modules in gaming and simulation subsystems are defined and interaction mechanisms established. Research and standards issues for implementation of the proposed architecture are discussed.
621323
Prudence in vacillatory language identification
This paper settles a question about “prudent” “vacillatory” identification of languages. Consider a scenario in which an algorithmic deviceM is presented with all and only the elements of a languageL, andM conjectures a sequence, possibly infinite, of grammars. Three different criteria for success ofM onL have been extensively investigated in formal language learning theory. IfM converges to a single correct grammar forL, then the criterion of success is Gold's seminal notion ofTxtEx-identification. IfM converges to a finite number of correct grammars forL, then the criterion of success is calledTxtFex-identification. Further, ifM, after a finite number of incorrect guesses, outputs only correct grammars forL (possibly infinitely many distinct grammars), then the criterion of success is known asTxtBc-identification. A learning machine is said to beprudent according to a particular criterion of success just in case the only grammars it ever conjectures are for languages that it can learn according to that criterion. This notion was introduced by Osherson, Stob, and Weinstein with a view to investigating certain proposals for characterizing natural languages in linguistic theory. Fulk showed that prudence does not restrictTxtEx-identification, and later Kurtz and Royer showed that prudence does not restrictTxtBc-identification. This paper shows that prudence does not restrictTxtFex-identification.
15041828
Language Learning with Some Negative Information
Gold-style language learning is a formal theory of learning from examples by algorithmic devices called learning machines. Originally motivated by child language learning, it features the algorithmic synthesis (in the limit) of grammars for formal languages from information about those languages. In traditional Gold-style language learning, learning machines are not provided with negative information, i.e., information about the complements of the input languages. We investigate two approaches to providing small amounts of negative information and demonstrate in each case a strong resulting increase in learning power. Finally, we show that small packets of negative information also lead to increased speed of learning. This result agrees with a psycholinguistic hypothesis of McNeill correlating the availability of parental expansions with the speed of child language development.
16360667
On some open problems in reflective inductive inference
In this paper we show that there exist classes of functions which can be learnt by a finite learner which reflects on its capability, but not learnable by a consistent learner which optimistically reflects on its capability. This solves the two mentioned open problems from [G. Grieser, Reflective inductive inference of recursive functions, Theoretical Computer Science A 397 (1-3) (2008) 57-69 (Special Issue on Forty Years of Inductive Inference. Dedicated to the 60th Birthday of Rolf Wiehagen)].
42287490
Program Synthesis in the Presence of Infinite Number of Inaccuracies
Most studies modeling inaccurate data in Gold style learning consider cases in which the number of inaccuracies is finite. The present paper argues that this approach is not reasonable for modelling inaccuracies in concepts that are infinite in nature (for example, graphs of computable functions). The effect of an infinite number of inaccuracies in the input data in Gold's model of learning is considered in the context of identification in the limit of computer programs from graphs of computable functions. Three kinds of inaccuracies, namely, noisy data, incomplete data, and imperfect data, are considered. The amount of each of these inaccuracies in the input is measured using certain density notions. A number of interesting hierarchy results are shown based on the densities of inaccuracies present in the input data. Several results establishing trade-offs between the density and type of inaccuracies are also derived.
7808014
One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples
As some cognitive research suggests, in the process of learning languages, in addition to overtexplicit negative evidence, a child often receives covertexplicit evidence in form of corrected or rephrased sentences. In this paper, we suggest one approach to formalization of overt and covert evidence within the framework of one-shotlearners via subset and membership queries to a teacher (oracle). We compare and explore general capabilities of our models, as well as complexity advantages of learnability models of one type over models of other types, where complexity is measured in terms of number of queries. In particular, we establish that "correcting" positive examples give sometimes more power to a learner than just negative (counter)examples and access to full positive data.