Learning and transfer in dynamic decision environments

An important aspect of learning is the ability to transfer knowledge to new contexts. However, in dynamic decision tasks, such as bargaining, firefighting, and process control, where decision makers must make repeated decisions under time pressure and outcome feedback may relate to any of a number of decisions, such transfer has proven elusive. This paper proposes a two-stage connectionist model which hypothesizes that decision makers learn to identify categories of evidence requiring similar decisions as they perform in dynamic environments. The model suggests conditions under which decision makers will be able to use this ability to help them in novel situations. These predictions are compared against those of a one-stage decision model that does not learn evidence categories, as is common in many current theories of repeated decision making. Both models' predictions are then tested against the performance of decision makers in an Internet bargaining task. Both models correctly predict aspects of decision makers' learning under different interventions. The two-stage model provides closer fits to decision maker performance in a new, related bargaining task and accounts for important features of higher-performing decision makers' learning. Although frequently omitted in recent accounts of repeated decision making, the processes of evidence category formation described by the two-stage model appear critical in understanding the extent to which decision makers learn from feedback in dynamic tasks. Faison (Bud) Gibson is an Assistant Professor at College of Business, Eastern Michigan University. He has extensive experience developing and empirically testing models of decision behavior in dynamic decision environments.     

Validation and verification of social processes within agent-based computational organization models

The use of simulation modeling in computational analysis of organizations is becoming a prominent approach in social science research. However, relying on simulations to gain intuition about social phenomena has significant implications. While simulations may give rise to interesting macro-level phenomena, and sometimes even mimic empirical data, the underlying micro and macro level processes may be far from realistic. Yet, this realism may be important to infer results that are relevant to existing theories of social systems and to policy making. Therefore, it is important to assess not only predictive capability but also explanation accuracy of formal models in terms of the degree of realism reflected by the embedded processes. This paper presents a process-centric perspective for the validation and verification (V&V) of agent-based computational organization models. Following an overview of the role of V&V within the life cycle of a simulation study, emergent issues in agent-based organization model V&V are outlined. The notion of social contract that facilitates capturing micro level processes among agents is introduced to enable reasoning about the integrity and consistency of agent-based organization designs. Social contracts are shown to enable modular compositional verification of interaction dynamics among peer agents. Two types of consistency are introduced: horizontal and vertical consistency. It is argued that such local consistency analysis is necessary, but insufficient to validate emergent macro processes within multi-agent organizations. As such, new formal validation metrics are introduced to substantiate the operational validity of emergent macro-level behavior. Levent Yilmaz is Assistant Professor of Computer Science and Engineering in the College of Engineering at Auburn University and co-founder of the Auburn Modeling and Simulation Laboratory of the M&SNet. Dr. Yilmaz received his Ph.D. and M.S. degrees from Virginia Polytechnic Institute and State University (Virginia Tech). His research interests are on advancing the theory and methodology of simulation modeling, agent-directed simulation (to explore dynamics of socio-technical systems, organizations, and human/team behavior), and education in simulation modeling. Dr. Yilmaz is a member of ACM, IEEE Computer Society, Society for Computer Simulation International, and Upsilon Pi Epsilon. URL: http://www.eng.auburn.edu/~yilmaz     

Finite turns and the regular closure of linear context-free languages

Turn bounded pushdown automata with different conditions for beginning a new turn are investigated. Their relationships with closures of the linear context-free languages under regular operations are studied. For example, automata with an unbounded number of turns that have to empty their pushdown store up to the initial symbol in order to start a new turn are characterized by the regular closure of the linear languages. Automata that additionally have to re-enter the initial state are (almost) characterized by the Kleene star closure of the linear languages. For both a bounded and an unbounded number of turns, requiring to empty the pushdown store is a strictly stronger condition than requiring to re-enter the initial state. Several new language families are obtained which form a double-stranded hierarchy. Closure properties of these families under AFL operations are derived. The regular closure of the linear languages share the strong closure properties of the context-free languages, i.e., the family is a full AFL. Interestingly, three natural new language families are not closed under intersection with regular languages and inverse homomorphism. Finally, an algorithm is presented parsing languages from the new families in quadratic time.     

Zur Theorie der Chiralitätsfunktionen

The Algebraic Theory of Chirality Functions is derived by means of exclusively qualitative considerations. Hence, the significance of quantitative results is questionable. Moreover the construction of “Näherungsansätze” (”Approximation-Ansatz”), which may be interpreted as semiempirical methods, is achieved on the basis of plausibility and mathematical simplicity. Since physical arguments are not included, the consistency or inconsistency of “Näherungsansätze” with experimental results do not justify direct physical conclusions.     

高温超导体制备条件的人工神经网络识别

高温超导体的制备条件要求严格,其掺杂量大小、烧结温度控制等都直接影响实验样本的超导性质。近几年高温超导研究已积累大量实验数据,如何应用人工智能方法处理这些数据寻找更好的合成条件颇有意义。人工神经网络方法在许多领域己显示其处理复杂数据和模式识别的优越性,但尚未应用到化合物制备研究方面。本文对此作了初步尝试。     

New method for calculating the adsorption of noble gases on amorphous surfaces

A new approach to calculating the equilibrium characteristics of the adsorption of noble gases on the amorphous surfaces of adsorbents was developed and applied to the Ar−TiO₂(rutile) system. Intermolecular adsorbate-adsorbate interactions are taken into account for the nearest neighbors in the quasi-chemical approximation. The lattice energy parameters of all interactions of the model are determined from the Lennard-Jones potential (12-6). The formation of amorphous TiO₂(rutile) surface includes completion of the surface layers and partial removal of the surface oxygen ions. The quality of the amorphization procedure was confirmed by the experimentally measured heats and isotherms of adsorption of the system under study. Translated fromIzvestiya Akademii Nauk. Seriya Khimicheskaya, No. 6, pp. 1109–1118, June, 1997.     

Preparation of cellulose samples for size-exclusion chromatography analyses in studies of paper degradation

Hydrolytic degradation of cellulose was shown to take place during the activation procedure in distilled water during the dissolution procedure of cellulose samples from papers for size-exclusion chromatography analyses in the lithium chloride-N,N-dimethylacetamide (DMAc) solution system. The use of dilute aqueous sodium hydroxide solution in the activation procedure prevents hydrolytic degradation of cellulose during the dissolution procedure, especially in the case of samples of aged papers with low pH. The use of the freeze-drying technique provides samples of cellulose ready-made for dissolution in lithium chloride-N,N-dimethylacetamide solution.     

Exact Fixed-node Quantum Monte Carlo： Self-optimizing Procedure

In this paper, a novel exact fixed-node quantum Monte Carlo (EFNQMC) algorithm was proposed, which is a self-optimizing and self-improving procedure. In contrast to the previous EFN-QMC method, the importance function of this method is optimized synchronistically in the diffusion procedure, but not be-fore beginning the EFNQMC computation. In order to optimize the importance function, the improved steepest descent tech-nique is used, in which the step size is automatically adjustable.The procedure is quasi-Newton type and converges super linear-ly. The present method also uses a novel trial function, which has correct electron-electron and electron-nucleus cusp condi-tious. The novel EFNQMC algorithm and the novel trial func-tion are employed to calculate the energies of 1 ^1A1 state of CH2, ^1Ag state of Cs and the ground-states of H2, LiH, Li2 and H2O.     

On-line testing of gas chromatographic columns with a programmable computing integrator

Summary A program is described which calculates the number of effective plates and the coating efficiency over the entire range of a test chromatogram. The peak widths at half height are derived by assuming a Gaussian peak shape. The interpolated peak width at k=4 is used for computing a standardized number of effective plates. Plate height, column permeability, overall performance and a novel parameter called sampling efficiency are calculated from 5 other figures — i. e. carrier gas code, pressure drop, column length, column temperature and particle size.Dedicated to Dr. Leslie S. Ettre for his 60th birthday.