An actor-critic algorithm for constrained Markov decision processes

An actor-critic type reinforcement learning algorithm is proposed and analyzed for constrained controlled Markov decision processes. The analysis uses multiscale stochastic approximation theory and the envelope theorem' of mathematical economics.     

The CADE-14 ATP System Competition

This paper documents the design, competing systems, results, and conclusions of the CADE-14 ATP System Competition (CASC-14).     

广义Foster定理

利用Ｍａｘｗｅｌｌ方程组导出了适用于有耗网络的广义Ｆｏｓｔｅｒ定理，得到了一些有关电抗斜率以及Ｑ值的有用公式及结论。     

Implicit induction in conditional theories

We propose a new procedure for proof by induction in conditional theories where case analysis is simulated by term rewriting. This technique reduces considerably the number of variables of a conjecture to be considered for applying induction schemes. Our procedure is presented as a set of inference rules whose correctness has been formally proved. Moreover, when the axioms are ground convergent and the functions are completely defined, it is possible to apply the system for refuting conjectures. The procedure is even refutationally complete for conditional equations with Boolean preconditions over free constructors. The method is entirely implemented in the proverSPIKE. This system has solved interesting problems in a completely automatic way, that is, without interaction with the user and without ad hoc heuristics. It has also proved the challenging Gilbreath card trick, with only two easy lemmas.Preliminary versions of the results have been presented at the 13th International Joint Conference on Artificial Intelligence, Chambéry (France), 1993 (Bouhoula and Rusinowith, 1993).     

基于车联网的隐私保护数据聚合研究综述

随着智能网联汽车的普及,用户数据的隐私问题成为了车联网发展中亟待解决的问题。针对车联网聚合方案的研究现状,对当前方案中存在的问题进行分析总结。首先,系统地介绍了车联网中主流系统模型和车联网中常见的攻击模型;其次,对当前国内外应用在车联网中的聚合方案的安全性、效率和优劣进行分析总结,分别从签名阶段聚合方案、用户数据收集和传输阶段聚合方案和云平台处理数据阶段聚合方案三方面对其进行讨论;最后,阐述了车联网聚合方案中存在的问题及解决方法,展望了车联网聚合方案未来的研究方向。     

Hybrid function projective synchronization of chaotic systems with uncertain time-varying parameters via Fourier series expansion

In this paper, the hybrid function projective synchronization (HFPS) of different chaotic systems with uncertain periodically time-varying parameters is carried out by Fourier series expansion and adaptive bounding technique. Fourier series expansion is used to deal with uncertain periodically time-varying parameters. Adaptive bounding technique is used to compensate the bound of truncation errors. Using the Lyapunov stability theory, an adaptive control law and six parameter updating laws are constructed to make the states of two different chaotic systems asymptotically synchronized. The control strategy does not need to know the parameters thoroughly if the time-varying parameters are periodical functions. Finally, in order to verify the effectiveness of the proposed scheme, the HFPS between Lorenz system and Chen system is completed successfully by using this scheme.     

A λ-unifiability test for set theory

We present a semi-decision algorithm for the unifiability of two set-theoretic formulas modulo -reduction. The algorithm is based on the approach developed by G. Huet for type theory, but requires additional measures because formulas in set theory are not all normalizable. We present the algorithm in an Ada-like pseudocode, and then prove two theorems that show the completeness and correctness of the procedure. We conclude by showing that -unification is not a complete quantifier substitution method for set theory-unlile first-order unification and first-order logic. In this respect set theory is similar to type theory (higher-order logic).This material is based upon work supported by the National Science Foundation under award number ISI-8560438. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author and do not necessarily reflect the views of the National Science Foundation.     

Higher-Order and Modal Logic as a Framework for Explanation-Based Generalization

Certain tasks, such as formal program development and theorem proving, fundamentally rely upon the manipulation of higher-order objects such as functions and predicates. Computing tools intended to assist in performing these tasks are at present inadequate in both the amount of knowledge they contain (i.e., the level of support they provide) and in their ability to learn (i.e., their capacity to enhance that support over time). The application of a relevant machine learning technique—explanation-based generalization (EBG)—has thus far been limited to first-order problem representations. We extend EBG to generalize higher-order values, thereby enabling its application to higher-order problem encodings.Logic programming provides a uniform framework in which all aspects of explanation-based generalization and learning may be defined and carried out. First-order Horn logics (e.g., Prolog) are not, however, well suited to higher-order applications. Instead, we employ Prolog, a higher-order logic programming language, as our basic framework for realizing higher-order EBG. In order to capture the distinction between domain theory and training instance upon which EBG relies, we extend Prolog with the necessity operator of modal logic. We develop a meta-interpreter realizing EBG for the extended language, Prolog, and provide examples of higher-order EBG.     

Modal logic as metalogic

The goal of this paper is to show how modal logic may be conceived as recording the derived rules of a logical system in the system itself. This conception of modal logic was propounded by Dana Scott in the early seventies. Here, similar ideas are pursued in a context less classical than Scott's.First a family of propositional logical systems is considered, which is obtained by gradually adding structural rules to a variant of the nonassociative Lambek calculus. In this family one finds systems that correspond to the associative Lambek calculus, linear logic, relevant logics, BCK logic and intuitionistic logic. Above these basic systems, sequent systems parallel to the basic systems are constructed, which formalize various notions of derived rules for the basic systems. The deduction theorem is provable for the basic systems if, and only if, they are at least as strong as systems corresponding to linear logic, or BCK logic, depending on the language, and their deductive metalogic is not stronger than they are.However, though we do not always have the deduction theorem, we may always obtain a modal analogue of the deduction theorem for conservative modal extensions of the basic systems. Modal postulates which are necessary and sufficient for that are postulates of S4 plus modal postulates which mimic structural rules. For example, the modal postulates which Girard has recently considered in linear logic are necessary and sufficient for the modal analogue of the deduction theorem.All this may lead towards results about functional completeness in categories. When functional completeness, which is analogous to the deduction theorem, fails, we may perhaps envisage a modal analogue of functional completeness in a modal category, of which our original category is a full subcategory.     

基于FLUENT的烘干机参数优化

为了解决烘干机烘室内气流分布不均匀,导致烘干成品质量参差不齐的问题,采用FLUENT软件和正交试验相结合的方法,以风速为评价指标,对不同参数下烘干房内的气流进行模拟分析。同时用极差分析法和标准差相结合的方法对评价指标进行分析,得出最佳的参数组合,并对其进行仿真模拟分析。结果表明:烘干房烤盘间距为10 mm、出风口大小1 000 mm×230 mm、进风流速为4.5 m/s时,烘干效果最好,为优化烘房设计参数的研究提供了理论依据。