1517191
Semantic resolution for e-commerce
We describe a research project on resolving semantic differences for multi-agent systems (MAS) in electronic commerce. The approach can be characterized as follows: (1) agents in a MAS may have their own specific ontologies defined on top of a shared base ontology; (2) concepts in these ontologies are represented as frame-like structures based on DAML+OIL language; (3) the semantic differences between agents are resolved at runtime through inter-agent communication; and (4) the resolution is viewed as an abductive inference process, and thus necessarily involves approximate reasoning.
9845111
Quantitative Agent Service Matching
The ultimate goal of service matching is to find the service provider(s) that would perform tasks of given description with the best overall degree of satisfaction. However, service description matching solves only part of the problem. Agents that match a given request may vary greatly in their actual capabilities to perform the tasks, and an agent may have strong and weak areas. In this work, we take a quantitative approach in which performance rating is considered an integral part of an agent's capability model and service distribution is taken into account in determining the degree of match. With the dynamic refinement of the agent capability model, the broker captures an agent's performance levels as well as its strong and weak areas. An experimental system has been designed and implemented within the OWL/OWL-S framework and the results statistics show significant advantage over other major levels of brokers.
723568
A Bayesian Network Approach to Ontology Mapping
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs. Probabilities needed for constructing conditional probability tables (CPT) during translation and for measuring semantic similarity during mapping are learned using text classification techniques where each concept in an ontology is associated with a set of semantically relevant text documents, which are obtained by ontology guided web mining. The basic ideas of this approach are validated by positive results from computer experiments on two small real-world ontologies.
7138939
A probabilistic extension to ontology language OWL
To support uncertain ontology representation and ontology reasoning and mapping, we propose to incorporate Bayesian networks (BN), a widely used graphic model for knowledge representation under uncertainty and OWL, the de facto industry standard ontology language recommended by W3C. First, OWL is augmented to allow additional probabilistic markups, so probabilities can be attached with individual concepts and properties in an OWL ontology. Secondly, a set of translation rules is defined to convert this probabilistically annotated OWL ontology into the directed acyclic graph (DAG) of a BN. Finally, the BN is completed by constructing conditional probability tables (CPT) for each node in the DAG. Our probabilistic extension to OWL is consistent with OWL semantics, and the translated BN is associated with a joint probability distribution over the application domain. General Bayesian network inference procedures (e.g., belief propagation or junction tree) can be used to compute P(C/spl bsol/e): the degree of the overlap or inclusion between a concept C and a concept represented by a description e. We also provide a similarity measure that can be used to find the most similar concept that a given description belongs to.
5485929
ITTALKS: A Case Study in the Semantic Web and DAML
Effective use of the vast quantity of information now available on the web will require the use of "Semantic Web" markup languages such as the DARPA Agent Markup Language (DAML). Such languages will enable the automated gathering and processing of much information that is currently available but insufficiently utilized. Effectively, such languages will facilitate the integration of multi-agent systems with the existing information infrastructure. As part of our exploration of Semantic Web technology, and DAML in particular, we have constructed ITTALKS, a web-based system for automatic and intelligent notification of information technology talks. In this paper, we describe the ITTALKS system, and discuss the numerous ways in which the use of Semantic Web concepts and DAML extend its ability to provide an intelligent online service to both the human community and the agents assisting them.
183316
Modifying Bayesian Networks by Probability Constraints
This paper deals with the following problem: modify a Bayesian network to satisfy a given set of probability constraints by only change its conditional probability tables, and the probability distribution of the resulting network should be as close as possible to that of the original network. We propose to solve this problem by extending IPFP (iterative proportional fitting procedure) to probability distributions represented by Bayesian networks. The resulting algorithm E-IPFP is further developed to D-IPFP, which reduces the computational cost by decomposing a global E-IPFP into a set of smaller local E-IPFP problems. Limited analysis is provided, including the convergence proofs of the two algorithms. Computer experiments were conducted to validate the algorithms. The results are consistent with the theoretical analysis.
6604689
Chromaticity of certain tripartite graphs identified with a path
For a graph G, let P(G) be its chromatic polynomial. Two graphs G and H are chromatically equivalent if P(G)=P(H). A graph G is chromatically unique if P(H)=P(G) implies that [email protected]?G. In this paper, we classify the chromatic classes of graphs obtained from K"2","2","[email protected]?P"m(m>=3), (K"2","2","2-e)@?P"m(m>=5) and (K"2","2","2-2e)@?P"m(m>=6) by identifying the end-vertices of the path P"m with any two vertices of K"2","2","2, K"2","2","2-e and K"2","2","2-2e, respectively, where e and 2e are, respectively, an edge and any two edges of K"2","2","2. As a by-product of this, we obtain some families of chromatically unique and chromatically equivalent classes of graphs.
21181741
An alternative estimation method for the accelerated failure time frailty model
Frailty models based on the proportional hazards model are useful to analyze correlated or clustered failure time data. However, there has been some recent interest in a frailty model based on the popular accelerated failure time model for correlated failure time data ([Pan, W., 2001. Using frailties in the accelerated failure time model. Lifetime Data Anal. 7(1), 55-64], for example). In this paper we review recent advances on this model in the literature. We propose a general estimation method based on M-estimators and the EM algorithm to estimate the parameters in the model. To evaluate the performance of the proposed method, we carry out a simulation study. The results of the simulation study show that the proposed method performs well in comparison with existing estimation methods. As an illustration, the model and the proposed method are applied to analyze the effects of sublingual nitroglycerin and oral isosorbide dinitrate on angina pectoris of coronary heart disease patients [Danahy, D.T., Burwell, D.T., Aronow, W.S., Prakash, R., 1977. Sustained hemodynamic and antianginal effect of high dose oral isosorbide dinitrate. Circulation 55, 381-387].
16284083
Minimizing Complexity in Cellular Automata Models of Self-Replication
Understanding self-replication from an information processing perspective is important because, among other things, it can shed light on molecular mechanisms of biological reproduction and on prebiotic chemical evolution. Intuition, biological knowledge, and early computational models of self-replication all suggested that self-replication is an inherently complex process. In this paper we describe recent computational studies that challenge this viewpoint. We summarize our recent work with cellular automata models of simple yet non-trivial self-replicating structures called unsheathed loops. For example, one unsheathed loop consists of only six components and requires only 20 rules to specify the local intercomponent interactions needed to bring about replication. The implication of this work is that, when viewed as an emergent property of numerous local, concurrent interactions between components, self-replicating systems can be substantially simpler than is generally recognized.
15008277
The interoperability problem: bringing together mobile agents and agent communication languages
Interoperability is a central issue far both the mobile agents community and the wider agents community. Unfortunately, the interoperability concerns are different between the two communities. As a result, inter-agent communication is an issue that has been addressed in a limited manner by the mobile agents community. Supplementing mobile agents with the ability to interact a a higher level with other mobile or static agents, or agentified information sources is a necessity in the vastly heterogeneous arena where mobile agents are called to compete. An agent communication language (ACL) has been interpreted by the agents community as a tool with the capacity to integrate disparate sources of information. Such a perspective does not seem to be shared by the mobile agents community. We investigate the origins of the differences of perspective on agent to agent communication and examine the reasons for the relative lack of interest on ACLs by mobile agents researchers and explore the integration of ACLs into mobile agents frameworks.
17328688
Improved Dataset Characterisation for Meta-learning
This paper presents new measures, based on the induced decision tree, to characterise datasets for meta-learning in order to select appropriate learning algorithms. The main idea is to capture the characteristics of dataset from the structural shape and size of decision tree induced from the dataset. Totally 15 measures are proposed to describe the structure of a decision tree. Their effectiveness is illustrated through extensive experiments, by comparing to the results obtained by the existing data characteristics techniques, including data characteristics tool (DCT) that is the most wide used technique in meta-learning, and Landmarking that is the most recently developed method.