Service interface description languages such as WSDL, and related standards, are evolving rapidly to provide a foundation for interoperation between Web services. At the same time, Semantic Web service technologies, such as the Ontology Web Language for Services (OWL-S), are developing the means by which services can be given richer semantic specifications. Richer semantics can enable fuller, more flexible automation of service provision and use, and support the construction of more powerful tools and methodologies. Both sets of technologies can benefit from complementary uses and cross-fertilization of ideas. This paper shows how to use OWL-S in conjunction with Web service standards, and explains and illustrates the value added by the semantics expressed in OWL-S.

https://eprints.soton.ac.uk/263000/1/OWL-S-SWSWPC2004-final.pdf

Bringing semantics to web services: the OWL-S approach

https://www.cs.umd.edu/~nau/papers/sirin2004htn.pdf

HTN planning for Web Service composition using SHOP2

A translation apparatus is provided which comprises: an inputting section for inputting a source document in a natural language; a layout analyzing section for analyzing layout information including cascade information, itemization information, numbered itemization information, labeled itemization information and separator line information in the source document inputted by the inputting section and specifying a translation range on the basis of the layout information; a translation processing section for translating a source document text in the specified translation range into a second language; and an outputting section for outputting a translated text provided by the translation processing section.

Automated Planning: Theory and Practice.

https://www.princeton.edu/~yael/Publications/BotvinickNivBarto2008.pdf

Hierarchically organized behavior and its neural foundations: A reinforcement learning perspective

Current industry standards for describing Web Services focus on ensuring interoperability across diverse platforms, but do not provide a good foundation for automating the use of Web Services. Representational techniques being developed for the Semantic Web can be used to augment these standards. The resulting Web Service specifications enable the development of software programs that can interpret descriptions of unfamiliar Web Services and then employ those services to satisfy user goals. OWL-S ("OWL for Services") is a set of notations for expressing such specifications, based on the Semantic Web ontology language OWL. It consists of three interrelated parts: a profile ontology, used to describe what the service does; a process ontology and corresponding presentation syntax, used to describe how the service is used; and a grounding ontology, used to describe how to interact with the service. OWL-S can be used to automate a variety of service-related activities involving service discovery, interoperation, and composition. A large body of research on OWL-S has led to the creation of many open-source tools for developing, reasoning about, and dynamically utilizing Web Services.

/pdf/bringing-semantics-to-web-services-with-owl-s-52kxa9d5zi.pdf

Bringing Semantics to Web Services with OWL-S

The SHOP2 planning system received one of the awards for distinguished performance in the 2002 International Planning Competition. This paper describes the features of SHOP2 which enabled it to excel in the competition, especially those aspects of SHOP2 that deal with temporal and metric planning domains.

/pdf/shop2-an-htn-planning-system-20n5kqaph4.pdf

SHOP2: an HTN planning system

We design the simple hierarchical ordered planner (SHOP) and its successor, SHOP2, with two goals in mind: to investigate research issues in automated planning and to provide some simple, practical planning tools. SHOP and SHOP2 are based on a planning formalism called hierarchical task network planning. SHOP and SHOP2 use a search-control strategy called ordered task decomposition, which breaks tasks into subtasks and generates the plan's actions in the same order that the plan executor executes them. So, throughout the planning process, the planner can tell what the state of the world at each step of the plan.

/pdf/applications-of-shop-and-shop2-3bx9pic6ve.pdf

Applications of SHOP and SHOP2

We present SADSR (security-aware adaptive DSR), a secure routing protocol for mobile ad hoc networks. SADSR authenticates the routing protocol messages using digital signatures based on asymmetric cryptography. The basic idea behind SADSR is to have multiple routes to each destination and store a local trust value for each node in the network. A trust value is assigned to each path based on trust values of the nodes which occur on that path. The paths with higher trust values are preferred for routing. We implemented our approach in ns2 simulator and compared the performance of SADSR and DSR. Our results show that in the presence of malicious nodes SADSR outperforms DSR in packet delivery ratio with an acceptable network load.

Security-aware adaptive dynamic source routing protocol

Previous algorithms for learning lexicographic preference models (LPMs) produce a "best guess" LPM that is consistent with the observations. Our approach is more democratic: we do not commit to a single LPM. Instead, we approximate the target using the votes of a collection of consistent LPMs. We present two variations of this method---variable voting and model voting---and empirically show that these democratic algorithms outperform the existing methods. We also introduce an intuitive yet powerful learning bias to prune some of the possible LPMs. We demonstrate how this learning bias can be used with variable and model voting and show that the learning bias improves the learning curve significantly, especially when the number of observations is small.

/pdf/democratic-approximation-of-lexicographic-preference-models-2gn6fzh9k5.pdf

Fusun Yaman

Papers

SHOP2: an HTN planning system

Applications of SHOP and SHOP2

Security-aware adaptive dynamic source routing protocol

Democratic approximation of lexicographic preference models

Democratic approximation of lexicographic preference models