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A planner infrastructure for semantic web enabled agents

Web services and agents are two important software development technologies that are affected from the semantic web innovation. Researches for attuning these topics to the semantic web prepare a ground for integration of them. In this paper, a planner infrastructure 1 is introduced that provides the integration of these two topics on the semantic web ground. Our approach is to support the semantic web service usage during agent planning process. Hence, agent can select required external semantic services to satisfy a goal and can interact with the selected services during the plan execution.

A generic testing framework for agent-based simulation models

Agent-based modelling and simulation (ABMS) had an increasing attention during the last decade. However, the weak validation and verification of agent-based simulation models makes ABMS hard to trust. There is no comprehensive tool set for verification and validation of agent-based simulation models, which demonstrates that inaccuracies exist and/or reveals the existing errors in the model. Moreover, on the practical side, many ABMS frameworks are in use. In this sense, we designed and developed a generic testing framework for agent-based simulation models to conduct validation and verification of models. This paper presents our testing framework in detail and demonstrates its effectiveness by showing its applicability on a realistic agent-based simulation case study.

An MAS infrastructure for implementing SWSA based semantic services

The Semantic Web Services Initiative Architecture (SWSA) describes the overall process of semantic service execution in three phases: discovery, engagement and enactment. To accomplish the specified requirements of these phases, it defines a conceptual model which is based on semantic service agents that provide and consume semantic web services and includes architectural and protocol abstractions. In this paper, an MAS infrastructure is defined which fulfills fundamental requirements of SWSAs conceptual model including all its sub-processes. Based on this infrastructure, requirements of a planner module is identified and has been implemented. The developed planner has the capability of executing plans consisting of special tasks for semantic service agents in a way that is described in SWSA. These special tasks are predefined to accomplish the requirements of SWSAs sub-processes and they can be reused in real plans of semantic service agents both as is and as specialized according to domain requirements.

Simulating Human Single Motor Units Using Self-Organizing Agents

Understanding functional synaptic connectivity of human central nervous system is one of the holy grails of the neuroscience. Due to the complexity of nervous system, it is common to reduce the problem to smaller networks such as motor unit pathways. In this sense, we designed and developed a simulation model that learns acting in the same way of human single motor units by using findings on human subjects. The developed model is based on self-organizing agents whose nominal and cooperative behaviors are based on the current knowledge on biological neural networks. The results show that the simulation model generates similar functionality with the observed data.

Engineering an MAS platform for semantic service integration based on the SWSA

In this paper, a Multi-Agent System (MAS) platform for semantic service integration based on the Semantic Web Services Initiative Architecture (SWSA) is discussed. We define a software architecture in order to provide concrete realization of the SWSA. The architecture fullfills fundamental requirements of the SWSAs sub-processes. Software agents are employed in automatic discovery and execution of the Semantic Web Services within this architecture. We also elaborate implementation of SWSAs sub-processes (service advertisement, discovery, engagement and enactment) taking the main components of the defined architecture and their interactions into consideration. Hence, the developers can easily utilize semantic web service technologies by using this flexible and extensible platform.

Developing multi agent systems on semantic web environment using SEAGENT platform

In this paper, we discuss the development of a multi agent system working on the Semantic Web environment by using a new framework called SEAGENT. SEAGENT is a new agent development framework and platform, which includes built-in features for semantic web based multi agent system development. These features provide semantic supports such as a new specific content language for transferring semantic knowledge, specifically designed agents internal architecture to handle semantic knowledge, a new directory facilitator architecture based on semantic service matching engine and ontology management service to provide ontology translations within the platforms ontologies. The implemented case study shows the effectiveness of these features in terms of semantically enriched multi agent system development.

An Infrastructure for the Semantic Integration of FIPA Compliant Agent Platforms

In this paper, an infrastructure for the semantic integration of FIPA compliant agent platforms is given*. The proposed infrastructure introduces two new architectural elements such as the platform directory service and the platform matcher which together support semantic matchmaking of remote platforms.

RatKit: Repeatable Automated Testing Toolkit for Agent-Based Modeling and Simulation

Agent-based modeling and simulation (ABMS) became an attractive and efficient way to model large-scale complex systems. The use of models always raises the question whether the model is correctly encoded (verification) and accurately represents the real system (validation). However, achieving a sufficiently credible agent-based simulation (ABS) model is still difficult due to weak verification, validation and testing (VV&T) techniques. Moreover, there is no comprehensive and integrated toolkit for VV&T of ABS models that demonstrates that inaccuracies exist and/or which reveals the existing errors in the model. Based on this observation, we designed and developed RatKit: a toolkit for ABS models to conduct VV&T. RatKit facilitates the VV&T process of ABMS by providing an integrated environment that allows repeatable and automated execution of ABS tests. This paper presents RatKit in detail and demonstrates its effectiveness by showing its applicability on a simple well-known case study: predator - prey.

Towards a broker agent in the semantic services environment

Brokers provide important discovery and synchronizationmechanisms among autonomous agents. Their mediation and coordinationproperties make brokers natural candidate components for thesemantic services environment where each service is described, discoveredand accessed semantically. However, brokers with rich functionalityof discovery and mediation are not part of the current semantic servicesenvironment. This paper discusses the design considerations of abroker agent in the semantic services environment. In this context, therequired services of this broker agent are analyzed, a multi-agent systeminfrastructure including such a broker agent for the semantic servicesenvironment is proposed and an interaction protocol, based on FIPAspecifications, for brokerage in this environment is given.

Semantically federating multi-agent organizations

We believe that successful co-operation between multi-agent systems providing services in a specific domain can be realized by constructing an infrastructure that supports the semantic interoperability between them. In this paper , we introduce a conceptual architecture for the semantic interoperability of multi-agent systems in the large-scale. The most important element of the proposed conceptual architecture is the federation. A federation established for a particular domain specifies the common characteristics of multi-agent systems in that domain. Hence, a special ontology is required at the federation level for defining the common characteristics of each multi-agent system in a particular domain as its own meta-knowledge. This meta-knowledge is then used in the semantic discovery of the multi-agent systems with which to co-operate. Since different multi-agent systems may use different ontologies, an ontology translation service is also defined at the federation level.