Abstract: This paper presents a new approach for intelligent agent communication based on ontology for agent community. DARPA agent markup language (DAML) is used to build the community ontology. This paper extends the agent management specification by the foundation for intelligent physical agents (FIPA) to develop an agent role called community facilitator (CF) that manages community directory and community ontology. CF helps build agent community. Precise description of agent service in this community can thus be achieved. This facilitates agent communication. Furthermore, through ontology update, agents with different ontology are capable of communicating with each other. An example of advanced traveler information system is included to illustrate practicality of this approach.
Abstract: The concept of flexible manufacturing is highly
appealing in gaining a competitive edge in the market by quickly
adapting to the changing customer needs. Scheduling jobs on flexible
manufacturing systems (FMSs) is a challenging task of managing the
available flexibility on the shop floor to react to the dynamics of the
environment in real-time. In this paper, an agent-oriented scheduling
framework that can be integrated with a real or a simulated FMS is
proposed. This framework works in stochastic environments with a
dynamic model of job arrival. It supports a hierarchical cooperative
scheduling that builds on the available flexibility of the shop floor.
Testing the framework on a model of a real FMS showed the
capability of the proposed approach to overcome the drawbacks of
the conventional approaches and maintain a near optimal solution
despite the dynamics of the operational environment.
Abstract: Alkali treated oil palm empty fruit bunch (EFB) fibres
(TEFBF) and untreated EFBF fibers (UEFBF) were incorporated in
polypropylene (PP) with and without malic anhydride grafted PP
(MAPP) and magnesium hydroxide as flame retardant (FR) to
produce TEFBF-PP and UEFBF-PP composites by the melt casting
method. The composites were characterized by mechanical and
burning tests along with a scanning electron microscope and Fourier
transform infrared spectroscopy. The significant improvement in
flexural modulus (133%) and flame retardant property (60%) of
TEFBF-PP composite with MAPP and FR is observed. The improved
mechanical property is discussed by the development of encapsulated
textures.
Abstract: Instead of representing individual cognition only, population cognition is represented using artificial neural networks whilst maintaining individuality. This population network trains continuously, simulating adaptation. An implementation of two coexisting populations is compared to the Lotka-Volterra model of predator-prey interaction. Applications include multi-agent systems such as artificial life or computer games.
Abstract: In this paper, we present the recently implemented approach allowing dynamics systems to plan its actions, taking into account the environment perception changes, and to control their execution when uncertainty and incomplete knowledge are the major characteristics of the situated environment [1],[2],[3],[4]. The control distributed architecture has three modules and the approach is related to hierarchical planning: the plan produced by the planner is further refined at the control layer that in turn supervises its execution by a functional level. We propose a new intelligent distributed architecture constituted by: Multi-Agent subsystem of the sensor, of the interpretation and representation of environment [9], of the dynamic localization and of the action. We tested this distributed architecture with dynamic system in the known environment. The autonomous for Rotor Mini Rotorcraft task is described by the primitive actions. The distributed controlbased on multi-agent system is in charge of achieving each task in the best possible way taking into account the context and sensory feedback.
Abstract: The purpose of the study reported here was designing Information Dissemination System (IDS) based E-learning in agricultural of Iran. A questionnaire was developed to designing Information Dissemination System. The questionnaire was distributed to 96 extension agents who work for Management of Extension and Farming System of Khuzestan province of Iran. Data collected were analyzed using the Statistical Package for the Social Sciences (SPSS). Appropriate statistical procedures for description (frequencies, percent, means, and standard deviations) were used. In this study there was a significant relationship between the age , IT skill and knowledge, years of extension work, the extend of information seeking motivation, level of job satisfaction and level of education with use of information technology by extension agent. According to extension agents five factors were ranked respectively as five top essential items to designing Information Dissemination System (IDS) based E-learning in agricultural of Iran. These factors include: 1) Establish communication between farmers, coordinators (extension agents), agricultural experts, research centers, and community by information technology. 2) The communication between all should be mutual. 3) The information must be based farmers need. 4) Internet used as a facility to transfer the advanced agricultural information to the farming community. 5) Farmers can be illiterate and speak a local and they are not expected to use the system directly. Knowledge produced by the agricultural scientist must be transformed in to computer understandable presentation. To designing Information Dissemination System, electronic communication, in the agricultural society and rural areas must be developed. This communication must be mutual between all factors.
Abstract: This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.
Abstract: Soccer simulation is an effort to motivate researchers and practitioners to do artificial and robotic intelligence research; and at the same time put into practice and test the results. Many researchers and practitioners throughout the world are continuously working to polish their ideas and improve their implemented systems. At the same time, new groups are forming and they bring bright new thoughts to the field. The research includes designing and executing robotic soccer simulation algorithms. In our research, a soccer simulation player is considered to be an intelligent agent that is capable of receiving information from the environment, analyze it and to choose the best action from a set of possible ones, for its next move. We concentrate on developing a two-phase method for the soccer player agent to choose its best next move. The method is then implemented into our software system called Nexus simulation team of Ferdowsi University. This system is based on TsinghuAeolus[1] team that was the champion of the world RoboCup soccer simulation contest in 2001 and 2002.
Abstract: In this paper, backup and recovery technique for Peer
to Peer applications, such as a distributed asynchronous Web-Based
Training system that we have previously proposed. In order to
improve the scalability and robustness of this system, all contents and
function are realized on mobile agents. These agents are distributed
to computers, and they can obtain using a Peer to Peer network
that modified Content-Addressable Network. In the proposed system,
although entire services do not become impossible even if some
computers break down, the problem that contents disappear occurs
with an agent-s disappearance. As a solution for this issue, backups
of agents are distributed to computers. If a failure of a computer is
detected, other computers will continue service using backups of the
agents belonged to the computer.
Abstract: In open settings, the participants in virtual
organization are autonomous and there is no central authority to
ensure the felicity of their interactions. When agents interact in such
settings, each relies upon being able to model the trustworthiness of
the agents with whom it interacts. Fundamentally, such models must
consider the past behavior of the other parties in order to predict their
future behavior. Further, it is sensible for the agents to share
information via referrals to trustworthy agents. In this article, trust is
a bet on the future contingent actions of others" and enumerates six
major factors supporting it: (1) reputation, (2) performance, (3)
appearance, (4) accountability, (5) precommitment, and (6)
contextual facilitation.
Abstract: Mature landfill leachates contain some macromolecular organic substances that are resistant to biological degradation. Recently, Fenton-s oxidation has been investigated for chemical treatment or pre-treatment of mature landfill leachates. The aim of this study was to reduce the recalcitrant organic load still remaining after the complete treatment of a mature landfill leachate by Fenton-s oxidation post-treatment. The effect of various parameters such as H2O2 to Fe2+ molar ratio, dosage of Fe2+ reagent, initial pH, reaction time and initial chemical oxygen demand (COD) strength, that have an important role on the oxidation, was analysed. A molar ratio H2O2/Fe2+ = 3, a Fe2+ dosage of 4 mmol·L-1, pH 3, and a reaction time of 40 min were found to achieve better oxidation performances. At these favorable conditions, COD removal efficiency was 60.9% and 31.1% for initial COD of 93 and 743 mg·L-1 respectively (diluted and non diluted leachate). Fenton-s oxidation also presented good results for color removal. In spite of being extremely difficult to treat this leachate, the above results seem rather encouraging on the application of Fenton-s oxidation.
Abstract: In this paper an open agent-based modular framework
for personalized and adaptive curriculum generation in e-learning
environment is proposed. Agent-based approaches offer several
potential advantages over alternative approaches. Agent-based
systems exhibit high levels of flexibility and robustness in dynamic
or unpredictable environments by virtue of their intrinsic autonomy.
The presented framework enables integration of different types of
expert agents, various kinds of learning objects and user modeling
techniques. It creates possibilities for adaptive e-learning process.
The KM e-learning system is in a process of implementation in
Varna Free University and will be used for supporting the
educational process at the University.
Abstract: A biocompatible ferrofluid have been prepared by coprecipitation
of FeCl2.4H2O and FeCl3.6H2O under ultrasonic
irradiation and with NaOH as alkaline agent. Cystein was also used
as capping agent in the solution. Magnetic properties of the produced
ferrofluid were then determined by VSM test and magnetite
nanoparticles were characterized by XRD and TEM techniques. The
effect of surfactant to Fe ion weight ratio was also studied during this
project by using two different amount of Dextran. Results showed the
presence of a biocompatible superparamagnetic ferrofluid including
magnetite nanoparticles with particle size ranging under 20 nm. The
increase in the surfactant content results in the narrowing of the size
distribution and reduction of the particle size and more solution
stability.
Abstract: The approaches to make an agent generate intelligent actions in the AI field might be roughly categorized into two ways–the classical planning and situated action system. It is well known that each system have its own strength and weakness. However, each system also has its own application field. In particular, most of situated action systems do not directly deal with the logical problem. This paper first briefly mentions the novel action generator to situatedly extract a set of actions, which is likely to help to achieve the goal at the current situation in the relaxed logical space. After performing the action set, the agent should recognize the situation for deciding the next likely action set. However, since the extracted action is an approximation of the action which helps to achieve the goal, the agent could be caught into the deadlock of the problem. This paper proposes the newly developed hybrid architecture to solve the problem, which combines the novel situated action generator with the conventional planner. The empirical result in some planning domains shows that the quality of the resultant path to the goal is mostly acceptable as well as deriving the fast response time, and suggests the correlation between the structure of problems and the organization of each system which generates the action.
Abstract: Bone growth factors, such as Bone Morphogenic
Protein-2 (BMP-2) have been approved by the FDA to replace grafting for some surgical interventions, but the high dose requirement limits its use in patients. Noggin, an extracellular protein, blocks the effect of BMP-2 by binding to BMP. Preventing
the BMP-2/noggin interaction will help increase the free
concentration of BMP-2 and therefore should enhance its efficacy to
induce bone formation. The work presented here involves
computational design of novel small molecule inhibitory agents of BMP-2/noggin interaction, based on our current understanding of
BMP-2, and its known putative ligands (receptors and antagonists). A
successful acquisition of such an inhibitory agent of BMP-2/noggin interaction would allow clinicians to reduce the dose required of
BMP-2 protein in clinical applications to promote osteogenesis. The
available crystal structures of the BMPs, its receptors, and the binding partner noggin were analyzed to identify the critical residues
involved in their interaction. In presenting this study, LUDI de novo design method was utilized to perform virtual screening of a large
number of compounds from a commercially available library against the binding sites of noggin to identify the lead chemical compounds
that could potentially block BMP-noggin interaction with a high specificity.
Abstract: Market based models are frequently used in the resource
allocation on the computational grid. However, as the size of
the grid grows, it becomes difficult for the customer to negotiate
directly with all the providers. Middle agents are introduced to
mediate between the providers and customers and facilitate the
resource allocation process. The most frequently deployed middle
agents are the matchmakers and the brokers. The matchmaking agent
finds possible candidate providers who can satisfy the requirements
of the consumers, after which the customer directly negotiates with
the candidates. The broker agents are mediating the negotiation with
the providers in real time.
In this paper we present a new type of middle agent, the marketmaker.
Its operation is based on two parallel operations - through
the investment process the marketmaker is acquiring resources and
resource reservations in large quantities, while through the resale process
it sells them to the customers. The operation of the marketmaker
is based on the fact that through its global view of the grid it can
perform a more efficient resource allocation than the one possible in
one-to-one negotiations between the customers and providers.
We present the operation and algorithms governing the operation
of the marketmaker agent, contrasting it with the matchmaker and
broker agents. Through a series of simulations in the task oriented
domain we compare the operation of the three agents types. We find
that the use of marketmaker agent leads to a better performance in the
allocation of large tasks and a significant reduction of the messaging
overhead.
Abstract: In this paper, a multi-agent robot system is presented. The system consists of four robots. The developed robots are able to automatically enter and patrol a harmful environment, such as the building infected with virus or the factory with leaking hazardous gas. Further, every robot is able to perform obstacle avoidance and search for the victims. Several operation modes are designed: remote control, obstacle avoidance, automatic searching, and so on.
Abstract: A new supported liquid membrane (SLM) system for
the selective transport of VO2
+ ions was prepared in this present
work. The SLM was a thin porous polyvinylidene difluoride
(PVDF) membrane soaked with Di-(2-ethylhexyl) phosphoric acid
(D2EHPA) as mobile carrier in Xylene as organic solvent.
D2EHPA acts as a highly selective carrier for the uphill transport of
VO2
+ ions through the SLM. The transport of VO2
+ ions reached to
64%. In the presence of P2O7-2 ion as suitable masking agent in the
feed solution, the interfering effects of other cations were eliminated.
Abstract: The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.
Abstract: The work reported in this paper proposes
Swarm-Array computing, a novel technique inspired by swarm
robotics, and built on the foundations of autonomic and parallel
computing. The approach aims to apply autonomic computing
constructs to parallel computing systems and in effect achieve the
self-ware objectives that describe self-managing systems. The
constitution of swarm-array computing comprising four constituents,
namely the computing system, the problem/task, the swarm and the
landscape is considered. Approaches that bind these constituents
together are proposed. Space applications employing FPGAs are
identified as a potential area for applying swarm-array computing for
building reliable systems. The feasibility of a proposed approach is
validated on the SeSAm multi-agent simulator and landscapes are
generated using the MATLAB toolkit.