38456449
NLG - Natural Language Graphics
The goal of the NLG project is to enhance person-computer interaction by using more than one mode of communication. The project uses a combination of natural language and graphics for both input and output. This allows development of practical, habitable systems suitable for users who are naive about programming, and encourages productive use of computers by more people. Mixed graphical and linguistic interaction could be an important tool in a variety of application areas.
13541175
Evaluating Network Serviceability
Abstract The capability to manage network operations on a day-to-day basis has become an important area of concern given the rapid expansion of computer networks. A related, but much less studied area, is the impact that the design of a network has on the ease with which it can be serviced. Evaluating the ease of servicing the network and its components does not concentrate on day-to-day operations of the network, but rather examines the network design over a longer term to identify problematic components, configurations and dependencies between components based on expert knowledge and historical data. This paper reports on our experience with a system to evaluate the ease of servicing a network—its serviceability—given a description of its design. The motivation for the work is that computer networks are more often “grown” than “designed” without concern for serviceability issues. The work also examines the impact of dependencies between components on the role of service and the potential disruption costs caused by these dependencies. This work is important because it is pro-active in explicitly considering the role of servicing a network when changing the components or configuration of a network. This approach is in contrast to network management, which is reactive in dealing with problems. The paper reports on a successful implementation of such as system and our experiences with it.
6315058
Knowledge and Control for a Mechanical Design Expert System
A new variety of Oriental hybrid lily plant bearing large upright-facing flowers particularly characterized by their clear pink coloration with deeper midribs, their large size and substance, and their upright to semi-upright orientation, the flowers being of excellent form and long persistence both on the plant and as cut flowers. This combination is completely new in the Oriental hybrid divisions of lilies suited to forcing and to mass commercial cultivation. The plant is an excellent garden plant, highly resistant to disease and shows tolerance of virus; the bulbs may be precooled and forced for cut flower production and the clone is vigorous, a good grower and a good propagator.
195710721
Special Issue: Machine Learning in Design
This issue of AIEDAM is based on a workshop on Machine Learning in Design held at the 1996 Conference on Artificial Intelligence in Design, AID'96 (Gero & Sudweeks, 1996), the third of such workshops, with the previous two being held at AID'92 (Gero, 1992) and at AID'94 (Gero & Sudweeks, 1994). The first two workshops also resulted in special issues of AIEDAM (Maher et al., 1994; Duffy et al., 1996).
7484630
A Graduate Level Expert Systems Course
This article presents an approach to a graduate-level course in expert, knowledge-based, problem-solving systems. The core of the course, and this article, is a set of questions called a profile, that can be used to characterize and compare each system studied.
14384022
Designing semantics-preserving cluster representatives for scientific input conditions
In scientific domains, knowledge is often discovered from experiments by grouping or clustering them based on the similarity of their output. The causes of similarity are analyzed based on the input conditions characterizing a given type of output, i.e., a given cluster. This analysis helps in applications such as decision support in industry. Cluster representatives form at-a-glance depictions for such applications. Randomly selecting a set of conditions in a cluster as its representative is not sufficient since distinct combinations of inputs could lead to the same cluster. In this paper, an approach called DesCond is proposed to design semantics-preserving cluster representatives for scientific input conditions. We define a notion of distance for conditions to capture semantics based on the types of their attributes and their relative importance. Using this distance, methods of building candidate cluster representatives with different levels of detail are proposed. Candidates are compared using the DesCond Encoding proposed in this paper that assesses their complexity and information loss, given user interests. The candidate with the lowest encoding for each cluster is returned as its designed representative. DesCond is evaluated with real data from Materials Science. Evaluation with domain expert interviews and formal user surveys shows that designed representatives consistently outperform randomly selected ones and different candidates suit different users.
16238835
Spatial agent‐based modelling
The convergence of object-oriented approaches to data modelling within geographic information science together with increasingly fine-scale data collection approaches and discrete-event simulations has created new opportunities to build dynamic representations of geographical systems (Gimblett 2002, Brown et al. 2005). In particular, agent-based modelling has become an important representational paradigm within both the biological (DeAngelis and Gross 1992) and social (Epstein and Axtell 1996) sciences. A software agent can be constructed as a selfdirected object, i.e. it has the ability to satisfy internal goals or objectives through actions and decisions based on a set of internal rules or strategies (Iglesias et al. 1999) and can be used in one of two primary modes: instrumental and representational. In the instrumental mode, agents are created for the primary purpose of performing a computing task to reduce reliance on the attention and cognition of a human operator, i.e. the agents stand in for the computer user. A good example is the system described by Sengupta and Bennett (2003) that uses agents to assist new users of geographic information systems in their application for decision support. In representational mode, the agent is designed for the primary purpose of behaving in a manner that is consistent with that of a third party, i.e. another person, group, institution, animal, or other animate object. Although this distinction is somewhat arbitrary and, in practice, not always clear, it highlights the range of purposes to which agent-based modeling is put within the articles presented here. This special issue draws together six papers that were presented at the GeoComputation 2005 conference, held on 1–3 August 2005 in Ann Arbor, Michigan and jointly hosted by the School of Natural Resources and Environment at the University of Michigan and the Institute for Geospatial Research and Education at Eastern Michigan University. As we surveyed the themes of papers presented at the conference, agent-based modelling was clearly a dominant one. Though the papers here tended to focus on issues associated with using agent-based modelling in representational mode, a couple of papers hinted at instrumental uses. For example, Parunak et al. discuss how agents can be used to solve the problems of navigation in heterogeneous landscapes, largely an instrumental application in which the agents perform computations collectively to solve complex spatial problems. Graniero and Robinson present a framework for building coupled agentlandscape models and illustrate the framework with representational agent-based
15121856
Agent-based and analytical modeling to evaluate the effectiveness of greenbelts
We present several models of residential development at the rural–urban fringe to evaluate the effectiveness of a greenbelt located beside a developed area, for delaying development outside the greenbelt. First, we develop a mathematical model, under two assumptions about the distributions of service centers, that represents the trade-off between greenbelt placement and width, their effects on the rate of development beyond the greenbelt, and how these interact with spatial patterns of aesthetic quality and the locations of services. Next, we present three agent-based models (ABMs) that include agents with the potential for heterogeneous preferences and a landscape with the potential for heterogeneous attributes. Results from experiments run with a one-dimensional ABM agree with the starkest of the results from the mathematical model, strengthening the support for both models. Further, we present two different two-dimensional ABMs and conduct a series of experiments to supplement our mathematical analysis. These include examining the effects of heterogeneous agent preferences, multiple landscape patterns, incomplete or imperfect information available to agents, and a positive aesthetic quality impact of the greenbelt on neighboring locations. These results suggest how width and location of the greenbelt could help determine the effectiveness of greenbelts for slowing sprawl, but that these relationships are sensitive to the patterns of landscape aesthetic quality and assumptions about service center locations. # 2004 Elsevier Ltd. All rights reserved.
2572723
Using a Markov network model in a univariate EDA: an empirical cost-benefit analysis
This paper presents an empirical cost-benefit analysis of an algorithm called Distribution Estimation Using MRF with direct sampling (DEUMd). DEUMd belongs to the family of Estimation of Distribution Algorithm (EDA). Particularly it is a univariate EDA. DEUMd uses a computationally more expensive model to estimate the probability distribution than other univariate EDAs. We investigate the performance of DEUMd in a range of optimization problem. Our experiments shows a better performance (in terms of the number of fitness evaluation needed by the algorithm to find a solution and the quality of the solution) of DEUMd on most of the problems analysed in this paper in comparison to that of other univariate EDAs. We conclude that use of a Markov Network in a univariate EDA can be of net benefit in defined set of circumstances.
5345095
A Parallel Genetic Heuristic for the Quadratic Assignment Problem
14214005
Incorporating a Metropolis method in a distribution estimation using Markov random field algorithm
Markov random field (MRF) modelling techniques have been recently proposed as a novel approach to probabilistic modelling for estimation of distribution algorithms (EDAs) (S. K. Shakya et al., 2004). An EDA using this technique was called distribution estimation using Markov random fields (DEUM). DEUM was later extended to DEUM/sub d/ (S. Shakya et al., 2005). DEUM and DEUM/sub d/ use a univariate model of probability distribution, and have been shown to perform better than other univariate EDAs for a range of optimization problems. This paper extends DEUM/sub d/ to incorporate a simple Metropolis method and empirically shows that for linear univariate problems the proposed univariate MRF models are very effective. In particular, the proposed DEUM/sub d/ algorithm can find the solution in O(n) fitness evaluations. Furthermore, we suggest that the Metropolis method can also be used to extend the DEUM approach to multivariate problems.