11698669
Modeling and verifying multi-agent behaviors using predicate/transition nets
In a multi-agent system, how agents accomplish a goal task is usually specified by multi-agent plans built from basic actions (e.g. operators) of which the agents are capable. A critical problem with such an approach is how can the designer make sure the plans are reliable. To tackle this problem, this paper presents a formal approach for modeling and analyzing multi-agent behaviors using Predicate/Transition (PrT) nets, a high-level formalism of Petri nets. We construct a multi-agent model by representing agent capabilities as transitions. To verify a multi-agent PrT model, we adapt the planning graphs as a compact structure for the reachability analysis. We also demonstrate that, based on the PrT model, whether parallel actions specified in multi-agent plans can be executed in parallel and whether the plans guarantee the achievement of the goal can be verified by analyzing the dependency relations among the transitions.
8292696
Human-agent teamwork for distributed team training
This paper presents an approach to human-agent mixed teams for distributed team training, demonstrated through the integration of the domain independent multiagent architecture CAST with the military command-and-control simulation software DDD (distributed dynamic decision-making). We extend the CAST architecture in a way such that agents can replace any number of teammates on a DDD team. To capture the overall picture of teamwork, we explore the MALLET language in CAST for the specification of team structures and processes that involve both humans and agents.
41800471
Ensuring Consistent Use/Misuse Case Decomposition for Secure Systems
11130686
An Aspect-Oriented Approach to Security Requirements Analysis
This paper presents an aspect-oriented approach to integrated elicitation of functional and security requirements based on use case-driven development. We identify security threats with respect to use cases and adopt threat mitigations for preventing or reducing security threats. To capture crosscutting nature of threats and mitigations, we specify them as aspects that encapsulate pointcuts and advice. A threat (mitigation) pointcut is a collection of join points in use cases at which the use cases are threatened (secured); whereas threat/mitigation advice describes how a threat can become an attack (can be mitigated). Eliciting threats and mitigations as aspects provides a structured way for separating functional and security concerns
18166781
A State-Based Approach to Testing Aspect-Oriented Programs
This paper presents a state-based approach to testing aspect-oriented programs. Aspectual state models, as an extension to the testable FREE state model of classes, are exploited to capture the impact of aspects on the state models of classes. To generate test suites for adequately testing object behavior and interaction between classes and aspects in terms of message sequences, we transform an aspectual state model to a transition tree, where each path from the root to some leaf node indicates a template of test cases, i.e. message sequences. Since the statebased approach is directly built upon the test design patterns for object-oriented programs, it is not only applicable to the simultaneous development of classes and aspects, but also to the incremental development of aspects based on the existing classes.
8230807
A Petri Net Based Software Architecture for UAV Simulation
This paper presents a Petri net-based hierarchical architecture for multiple Unmanned Aerial Vehicle (UAV) simulations in order to facilitate rapid prototyping via visual modeling and analysis. Using high-level Colored Petri nets, we specify UAV control structure by a hierarchy of mission control net and task nets: the mission control net, built upon task nets, models the decision making process of the UAV simulation; tasks nets are built from primitive UAV behaviors and environmental behaviors. To realize effects of UAV behaviors on the simulation environment, procedures may be associated with transitions in Petri nets. To demonstrate the approach, we describe two experimental UAV mission scenarios: sweeping search and multi-point attack.
8195983
Poisson shape interpolation
In this paper, we propose a novel shape interpolation approach based on Poisson equation. We formulate the trajectory problem of shape interpolation as solving Poisson equations defined on a domain mesh. A non-linear gradient field interpolation method is proposed to take both vertex coordinates and surface orientation into account. With proper boundary conditions, the in-between shapes are reconstructed implicitly from the interpolated gradient fields, while traditional methods usually manipulate vertex coordinates directly. Besides of global shape interpolation, our method is also applicable to local shape interpolation, and can be further enhanced by incorporating with deformation. Our approach can generate visual pleasing and physical plausible morphing sequences with stable area and volume changes. Experimental results demonstrate that our technique can avoid the shrinkage problem appeared in linear shape interpolation.
16692811
PType System: A Featherweight Parallelizability Detector
Parallel programming is becoming an important cornerstone of general computing. In addition, type systems have significant impact on program analysis. In this paper, we demonstrate an automated type- based system that soundly detects parallelizability of sequential func- tional programs. Our type inference system discovers the parallelizability property of a sequential program in a modular fashion, by exploring a ring structure among the program's operators. It handles self-recursive functions with accumulating parameters, as well as a class of non-linear mutual-recursive functions. Programs whose types are inferred to be par- allelizable can be automatically transformed to parallel code in a mutu- morphic form - a succint model for parallel computation. Transforming into such a form is an important step towards constructing efficient data parallel programs.
37194320
The evidential reasoning approach for multi-attribute decision analysis under interval uncertainty
Abstract The evidential reasoning (ER) approach is a method for multiple attribute decision analysis (MADA) under uncertainties. It improves the insightfulness and rationality of a decision making process by using a belief decision matrix (BDM) for problem modelling and the Dempster–Shafer (D–S) theory of evidence for attribute aggregation. The D–S theory provides scope and flexibility to deal with interval uncertainties or local ignorance in decision analysis, which is not explored in the original ER approach and will be investigated in this paper. Firstly, interval uncertainty will be defined and modelled in the ER framework. Then, an extended ER algorithm, IER, is derived, which enables the ER approach to deal with interval uncertainty in assessing alternatives on an attribute. It is proved that the original ER algorithm is a special case of the IER algorithm. The latter is demonstrated using numerical examples.
196020410
Distributed Partial Information Management (DPIM) schemes for survivable networks - Part I
2839172
A framework of fuzzy diagnosis
Fault diagnosis has become an important component in intelligent systems, such as intelligent control systems and intelligent elearning systems. Reiter's diagnosis theory, described by first-order sentences, has been attracting much attention in this field. However, descriptions and observations of most real-world situations are related to fuzziness because of the incompleteness and the uncertainty of knowledge, e.g., the fault diagnosis of student behaviors in the elearning processes. In this paper, an extension of Reiter's consistency-based diagnosis methodology, fuzzy diagnosis, has been proposed, which is able to deal with incomplete or fuzzy knowledge. A number of important properties of the fuzzy diagnoses schemes have also been established. The computing of fuzzy diagnoses is mapped to solving a system of inequalities. Some special cases, abstracted from real-world situations, have been discussed. In particular, the fuzzy diagnosis problem, in which fuzzy observations are represented by clause-style fuzzy theories, has been presented and its solving method has also been given. A student fault diagnostic problem abstracted from a simplified real-world elearning case is described to demonstrate the application of our diagnostic framework.