Sensors + agents + networks = aware agents

Software agents are being deployed in increasing numbers to help users find and manage information, particularly in open environments such as the Internet. For the most part, they operate independently and are typically designed to be aware only of their users and the environment in which they perform their tasks. Thus, they fail to take advantage of each other's abilities or results. For example, a shopping agent might periodically access several online databases to find the best price for a music CD and then purchase it if the price falls below its user's threshold. Other agents might be tracking prices for the same CD, duplicating each other's work. Similarly, if your agent and an agent for the person in the next cubicle are both browsing the same Web site, two identical data streams arrive on your LAN, using twice the bandwidth actually needed. To be more effective, agents must be aware of each other; therefore, they must acquire models of each other. One way to do this is by exchanging messages. A second form of awareness involves the state of the agent's own environment, including characteristics of the computer on which it is executing and its network connection. A third involves self awareness: knowing its name, age, ontology, goals, areas of expertise and ignorance, and reasoning abilities. Finally, the agent should be aware of its physical environment. The article explains how software agents can develop awareness     

Queries = examples + counterexamples

Database queries can be expressed as unordered collections of examples and counterexamples. The resulting languages are intuitive, first order complete, and applicable to a variety of data models including relational, object oriented, and visual models. This class of languages based on examples and counterexamples employ a minimal number of constructs with no sequencing or nesting of the constructs implied, allowing a simple and uniform theoretical analysis of their syntax, semantics, and completeness.     

Numbers Don’t Lie: 1+1=1, 1+1=2, 1+1=3

“Do you think that’s air you’re breathing?”A question posed by Morpheus to Neo in the movie The Matrix.I have a name for my pain and that name is ‘reality.’ What is real? Can you prove that its real? What constitutes proof? And if you can prove that it’s real, I may not accept your version of reality. For example, you may logically prove all foxes are green. I know some that are brunette. Take the mathematical equations in the title. Is the first one true or false? It’s true. In marriage, the union of a man and a woman makes one (social unit). Is the second equation true or false? True again. One person plus one person equals two persons. Is the third equation true or false? It’s also true. Take a man and a woman, add some pixie dust, and poof! You have a child, the third member of a social unit. No, I haven’t gone potty or gone mad trying to solve Mensa puzzles.     

Induction=I-Axiomatization+First-Order Consistency

In the early 1980s, there was a number of papers on what should be called proofs by consistency. They describe how to perform inductive proofs, without using an explicit induction scheme, in the context of equational specifications and ground-convergent rewrite systems. The method was explicitly stated as a first-order consistency proof in the case of pure equational, constructor-based specifications. In this paper, we show how, in general, inductive proofs can be reduced to first-order consistency and hence be performed by a first-order theorem prover. Moreover, we extend previous methods, allowing nonequational specifications (even non-Horn specifications) and designing some specific strategies. Finally, we also show how to drop the ground convergence requirement (which is called Saturatedness for general clauses).     

PSO + FL = PAASO: particle swarm optimization + federated learning = privacy-aware agent swarm optimization

International Journal of Information Security - In this paper, we present an unified framework that encompasses both particle swarm optimization (PSO) and federated learning (FL). This unified...     

Real-time information integrity = system integrity + data integrity + continuous assurances

A majority of companies today are totally dependent on their information assets, in most cases stored, processed and communicated within information systems in digital format. These information systems are enabled by modern information and communication technologies. These technologies are exposed to a continuously increasing set of risks. Yet, management and stakeholders continuously make important business decisions on information produced in real-time from these information systems. This information is unaccompanied by objective assurances as the current auditing procedures provide assurances months later. Therefore, risk management, including a system of internal controls, has become paramount to ensure the information's integrity. A system of internal controls, including IT controls at its core, help limit uncertainty and mitigate the risks to an acceptable level. Auditors play an increasingly important role in providing independent assurances that the information system's infrastructure and data maintain their integrities. These assurances include proposed new methods such as continuous auditing for assurance on demand.     

Object data MODEL = object-oriented + semantic models

The term ‘object-oriented database’ has been used to refer to different characteristics and mechanisms supported by semantic databases and (behaviorally) object-oriented ones. While this indicates the current confusion due to the lack of a common model, it also suggests the potential desirability of combining these two kinds of modeling facilities into the same nutshell. This paper summarizes from these two paradigms the features common to both, the features influenced/adopted by each other, and the features which are presented in one paradigm but missing from the other. After a brief analysis and discussion of these features, we conclude this paper by proposing our major theme: a complete object data model should take the union of the facilities offered by these two kinds of models.     

WFS + branch and bound = stable models

Though the semantics of nonmonotonic logic programming has been studied extensively, relatively little work has been done on operational aspects of these semantics. In this paper, we develop techniques to compute the well-founded model of a logic program. We describe a prototype implementation and show, based on experimental results, that our technique is more efficient than the standard alternating fixpoint computation. Subsequently, we develop techniques to compute the set of all stable models of a deductive database. These techniques first compute the well-founded semantics and then use an intelligent branch and bound strategy to compute the stable models. We report on our implementation, as well as on experiments that we have conducted on the efficiency of our approach     

PX systems = P systems + X machines

The paper is a survey of the main features of P systems, X machines and of a new computational device called PX system. The sequential and the parallel PX systems are presented. Results reflecting the computational power of these models and their effectiveness in solving NP-complete problems are briefly mentioned.     

Real-time system = discrete system + clock variables

This paper introduces, gently but rigorously, the clock approach to real-time programming. We present with mathematical precision, assuming no prerequisites other than familiarity with logical and programming notations, the concepts that are necessary for understanding, writing, and executing clock programs. In keeping with an expository style, all references are clustered in bibliographic remarks at the end of each section. The first appendix presents proof rules for verifying temporal properties of clock programs. The second appendix points to selected literature on formal methods and tools for programming with clocks. In particular, the timed automaton, which is a finite-state machine equipped with clocks, has become a standard paradigm for real-time model checking; it underlies the tools HyTech, Kronos, and Uppaal, which are discussed elsewhere in this volume.     

Interference logic = conditional logic + frame axiom

We investigate the notion of interference between formulas as a basis for change operations. Such a notion permits us to enrich conditional logics with a frame axiom. This new logic allows us to solve in a natural way some of the problems appearing in the model based approach to change. © 1994 John Wiley & Sons, Inc.     

On the fuzzy difference equation xn+1 = A+B/xn

 In this paper we study the existence the oscillatory behavior the boundedness and the asymptotic behavior of the positive solutions of the fuzzy equation x _n+1 =A+B/x _n ,n=0,1,… where x _n is a sequence of fuzzy numbers, A, B are fuzzy numbers.     

Disjunctive LP+integrity constraints= stable model semantics

We show that stable models of logic programs may be viewed as minimal models of programs that satisfy certain additional constraints. To do so, we transform the normal programs into disjunctive logic programs and sets of integrity constraints. We show that the stable models of the normal program coincide with the minimal models of the disjunctive program thatsatisfy the integrity constraints. As a consequence, the stable model semantics can be characterized using theextended generalized closed world assumption for disjunctive logic programs. Using this result, we develop a bottomup algorithm for function-free logic programs to find all stable models of a normal program by computing the perfect models of a disjunctive stratified logic program and checking them for consistency with the integrity constraints. The integrity constraints provide a rationale as to why some normal logic programs have no stable models.     

Evolutionary algorithms + domain knowledge = real-world evolutionary computation

We discuss implicit and explicit knowledge representation mechanisms for evolutionary algorithms (EAs). We also describe offline and online metaheuristics as examples of explicit methods to leverage this knowledge. We illustrate the benefits of this approach with four real-world applications. The first application is automated insurance underwriting-a discrete classification problem, which requires a careful tradeoff between the percentage of insurance applications handled by the classifier and its classification accuracy. The second application is flexible design and manufacturing-a combinatorial assignment problem, where we optimize design and manufacturing assignments with respect to time and cost of design and manufacturing for a given product. Both problems use metaheuristics as a way to encode domain knowledge. In the first application, the EA is used at the metalevel, while in the second application, the EA is the object-level problem solver. In both cases, the EAs use a single-valued fitness function that represents the required tradeoffs. The third application is a lamp spectrum optimization that is formulated as a multiobjective optimization problem. Using domain customized mutation operators, we obtain a well-sampled Pareto front showing all the nondominated solutions. The fourth application describes a scheduling problem for the maintenance tasks of a constellation of 25 low earth orbit satellites. The domain knowledge in this application is embedded in the design of a structured chromosome, a collection of time-value transformations to reflect static constraints, and a time-dependent penalty function to prevent schedule collisions.     

Effective Memetic Algorithms for VLSI design = Genetic Algorithms + local search + multi-level clustering

Combining global and local search is a strategy used by many successful hybrid optimization approaches. Memetic Algorithms (MAs) are Evolutionary Algorithms (EAs) that apply some sort of local search to further improve the fitness of individuals in the population. Memetic Algorithms have been shown to be very effective in solving many hard combinatorial optimization problems. This paper provides a forum for identifying and exploring the key issues that affect the design and application of Memetic Algorithms. The approach combines a hierarchical design technique, Genetic Algorithms, constructive techniques and advanced local search to solve VLSI circuit layout in the form of circuit partitioning and placement. Results obtained indicate that Memetic Algorithms based on local search, clustering and good initial solutions improve solution quality on average by 35% for the VLSI circuit partitioning problem and 54% for the VLSI standard cell placement problem.     

Numerical solution of the matrix equation AX + XAT+ B = 0

A recursive algorithm is shown to solve the above equation accurately for large (n leq 146), lightly damped (zeta geq 10^{-3}) systems. About2.5n^{2}storage locations are required, and about2.5n^{3}multiplications are performed per recursion, ten recursions being typical.