Title: Preface
<br>Cover Date: 2025-01-01
<br>Cover Display Date: 2025
<br>DOI: N/A
<br>Description: N/A
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: Preface
<br>Cover Date: 2025-01-01
<br>Cover Display Date: 2025
<br>DOI: N/A
<br>Description: N/A
<br>Citations: 0
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<br><br><br>Title: Message from General Chair
<br>Cover Date: 2024-01-01
<br>Cover Display Date: 2024
<br>DOI: 10.1109/iSAI-NLP64410.2024.10799247
<br>Description: N/A
<br>Citations: 0
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: TRENDS OF PAYOFFS OF AGENTS IN BAKERY GAME UNDER NON-COOPERATIVE ENVIRONMENT
<br>Cover Date: 2023-02-01
<br>Cover Display Date: February 2023
<br>DOI: 10.24507/icicel.17.02.153
<br>Description: Strategic form game (SFG) has been used widely to model inter-related decision making. Generally, researchers work on a particular game, specified by certain actions and corresponding payoffs. In real world, the situation can be much more complex, and a particular game may not be enough. Furthermore, the actions and payoffs are not known a priori. Here, we consider a more realistic environment, where payoffs are to be optimally computed from given resources and be used by agent for making decision. We are interested in wider spectrum of outcomes in games, where payoffs can vary within a trend such that the agents’ strategies remain unchanged. The results show that there exist certain ranges of resources that agents do not change their strategies. Hence, agents receive fair payoffs. Furthermore, taking into account additional computations that normally take place in real world environments does not affect the acceptable computation time for agent payoffs.
<br>Citations: 0
<br>Aggregation Type: Journal
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<br><br><br>Title: Planning Strategy of BDI Agents for Crowd Simulation
<br>Cover Date: 2023-01-01
<br>Cover Display Date: 2023
<br>DOI: 10.1007/978-3-031-36402-0_43
<br>Description: Crowd simulation has been an interesting and important area of research because of its wide application in real world domains. The driving mechanisms of crowd simulation is how agents in the crowd make decision about their individual moves. There can be many decisive factors, both internal and external, about how agents plan to move. In this research, we preliminarily examine how the collective crowds behave given that some agents have their behaviors different from other agents. With our BDI-based agents, we experimented with three types of individual behaviors: agressive, active and humble. We also have three types of traits: psychoticism, extraversion and neuroticism. We compare our BDI-based agents against RVO agents in different scenes. We find that in pass-through scenes, our agents can move faster to their destinations. In hallway scenes, our agents can move smoother and faster to their destinations. In narrowing passage scenes, our agents with agressive behaviors move faster than RVO agents. However, our agents with active and humble behaviours move slower than RVO agents.
<br>Citations: 1
<br>Aggregation Type: Book Series
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<br><br><br>Title: COLLISION AVOIDANCE AND PATH PLANNING IN CROWD SIMULATION
<br>Cover Date: 2023-01-01
<br>Cover Display Date: January 2023
<br>DOI: 10.24507/icicel.17.01.13
<br>Description: Modern crowd simulation needs two important characteristics: i) capability to simulate how human beings plan their paths, and ii) capability to cope with a large number of agents, particularly, in congested areas. Most research in this area does not focus on both issues at the same time because it can be computationally expensive. This research proposes a framework for crowd simulation that embraces these two capabilities and offers low computational cost. We combine BDI (Belief-Desire-Intention) model for planning and making decision, and RVO (Reciprocal Velocity Obstacle) for coping with congested areas. We achieve satisfactory results as a large number of agents can be simulated smoothly. We found that by combining BDI with RVO, the simulation time, i.e., how fast agents can move, is at least 20% faster in all scenarios. The execution time is also reduced dramatically, 35% on average. We can simulate up to 40,000 agents in a large scale area in a typical computer. The framework allows for visualized simulation of 600 agents at 24 frames per second and can go up to 6,400 agents at 1.5 frames per second.
<br>Citations: 9
<br>Aggregation Type: Journal
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<br><br><br>Title: PREDICTING KEY FACTORS IN AGRICULTURAL DATABASES FOR THAI FARMERS TO MAKE THE RIGHT DECISION
<br>Cover Date: 2023-01-01
<br>Cover Display Date: January 2023
<br>DOI: 10.24507/icicel.17.01.1
<br>Description: In recent years, Artificial Intelligence (AI) has been widely adopted to real world applications on several domains. The Department of Agriculture Extension (DOAE) of Thailand has courageously developed a large AI-based system, namely, Personalized Data (PD), in order to deliver suggestions to millions of Thai farmer in a convenient, affordable and timely fashion. While typical AI research expects experimental datasets and consumes a lot of time, this research investigates how such a system can deliver the required capabilities. There are three key factors, price, cost and yields of crops to be analyzed, in order to make it simple but meaningful to farmers. We found that artificial neural network with Multilayer Perceptron (MLP) and Random Forest (RF) models could effectively predict yield, cost, and price of crops. Adjusting parameters such as learning rate and the number of hidden nodes affect the accuracy of crop yield predictions. Smaller data sets required fewer hidden layers in model optimization. MLP models consistently produced more accurate yield predictions than RF models. MAPE (Mean Absolute Percentage Error) is used to measure both RF and MLP. It is found that MLP models produce accurate predictions. Similarly, RF is used to provide suggestions when time constraints are tight. We found that the accuracy is very high, and MAPE is around 5% in most cases. In some difficult scenarios where data is not adequate, the results are still good, and MAPE is around 20%.
<br>Citations: 0
<br>Aggregation Type: Journal
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<br><br><br>Title: COALITION FORMATION OF BUYERS IN REAL WORLD AGRICULTURE DOMAIN
<br>Cover Date: 2022-11-01
<br>Cover Display Date: November 2022
<br>DOI: 10.24507/icicelb.13.11.1143
<br>Description: This work presents algorithms for coalition formation of buyers in agriculture domain, where farmers use an application on their mobile phones to buy fertilizers (or other resources) in group and benefit from fair distribution of discounts. We propose algorithms that i) help farmers to form optimal coalitions of buyers, and ii) calculate Shapley value for fair distribution of discount among farmers in timely fashion. Since computing Shapley value can be intractable for even a small input, most researches tend to approximate the value. We compare our algorithm for computing Shapley value with other recent works and find that ours performs better in most cases. Particularly, our algorithm is faster for cases of 5-15 agents, which are more often. In cases of 19-20 agent, which seldom happen, ours is slightly slower but is still within seconds. This is due to the fact that ours works in non-structured data, which is more difficult to compute, while the others expect structured data. This shows that our algorithm can deliver results in timely fashion. To our best knowledge, there is no other system that serves individual farmers with this advanced technique. In addition, other related parties can also benefit from this system.
<br>Citations: 0
<br>Aggregation Type: Journal
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<br><br><br>Title: Computing Nash Equilibrium of Crops in Real World Agriculture Domain
<br>Cover Date: 2022-01-01
<br>Cover Display Date: 2022
<br>DOI: 10.1007/978-3-031-20992-5_1
<br>Description: Since the emergence of game theory as an area of research in artificial intelligence (AI), a lot of progress has been made over the years and is yet to be adopted in agriculture domain. The Department of Agriculture Extension (DOAE), Ministry of Agriculture, Thailand, has launched an innovative AI-based system, namely, Personalized Data (PD), to provide farmers with analyzed data through mobile applications. Among many features, the first and foremost is to provide information to DOAE officer to help decide for appropriate policies. As part of PD, a very important system for analyzing balance between yields and prices of crops, has also been developed. This system deploys Nash Equilibrium as a principle to help find balances among crops so that further policies can be examined and declared. Nash equilibrium has been widely adopted but not many has been applied in agriculture domains and more interestingly through mobile applications for farmers. This paper presents the NE-based system and its analytic results on pragmatic use under real world conditions. The approach used strictly follows Nash equilibrium as a preliminary tool for more complex analysis in later stage. The results show that the computation complexity is exponential. Combinations of 5 crops can take days to find equilibrium. Due to this nature, it is found that combinations of 3 crops is reasonable and bearable to real world usage.
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: Stable Coalitions of Buyers in Real World Agriculture Domain
<br>Cover Date: 2022-01-01
<br>Cover Display Date: 2022
<br>DOI: 10.1007/978-3-031-20992-5_16
<br>Description: The Department of Agricultural Extension, Ministry of Agriculture, Thailand, has developed and deployed an AI-based system, namely, Personalized Data (PD), to help millions of Thai farmers to make better decisions with regards to growing and selling crops. One of the AI module equipped with the system applies cooperative game theoretic principles, namely Kernel, a stability concept, as important part of the system. While most applications of game theory in real world domains concentrate on one game setting, this system may have to scan for much larger search space to ensure stability. This paper examines how much time it take and how large the search space can be in order to examine stability in practice. Although there are several algorithms involved, we present only ones for generating coalitions and examining whether the given payoff configuration is in Kernel. The former repeatedly generates all coalitions of a given set of agents. The latter compares between each pair of agents in every coalition of the given configuration payoff whether one of the agent’s payoff outweighs the other’s. For the search space of 15–30 agents, we find that it can range from 11 to 20 <sup>∘</sup> C of magnitude. For execution time, we find that it takes minutes for up to 18 agents and it takes hours for 19 agents. For larger number of agents, it can take days or months and will require a much more powerful computer to reduce the execution time.
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: News Feed: A Multiagent-Based Push Notification System
<br>Cover Date: 2022-01-01
<br>Cover Display Date: 2022
<br>DOI: 10.1007/978-3-031-20992-5_11
<br>Description: This document explains a very innovative multiagent-based information system driving personalized data to millions of farmers in Thailand. There are three main agents working in the system. The collective agent collects initial data from large databases and farmers. The analytic agent receives initial data and analyzes it for related keywords and sends them back to the collective agent. The key words are used to search for related external source of data that are useful and appropriately fit to individual needs and interests of farmers. The disperse agent then distributes the data to farmers, categorized into seven layers. Farmers benefit from these sets of information in many ways, including how to plant, grow, maintain and fertile until harvest. Even before planting, the system helps farmers to decide which crops they should choose. After harvesting, the system helps finding appropriate market for their crops.
<br>Citations: 1
<br>Aggregation Type: Book Series
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<br><br><br>Title: Improving Safety and Efficiency for Navigation in Multiagent Systems
<br>Cover Date: 2021-01-01
<br>Cover Display Date: 2021
<br>DOI: 10.1007/978-3-030-80253-0_16
<br>Description: Multiagent system concept can be deployed in many real world applications. A good example is unmanned aerial vehicle (UAV). While UAV deployment in real world has gained more popularity, many areas of research are still needed for more efficient, more useful, safer and more environment-friendly deployment of UAVs. The first and foremost issue is the navigation problem. Here, we investigate how to navigate UAVs through congested 3D sphere towards their individual destinations efficiently and safely. Our approach is based on 3D reciprocal velocity obstacle (3DRVO) and intelligent agent’s Belief-Desire-Intention (BDI) architecture. We represent UAVs by intelligent agents using 3DRVO at low level navigation for safety, and BDI at high level planning for efficiency. The simulation results show that agents can travel safely to their destinations. The results also show that the agents can travel efficiently, i.e., while the number of agents increases, the elapsed time for simulation and the simulation rounds increase in much lower rates.
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: A Multiagent-based Video Tracking Algorithm
<br>Cover Date: 2018-12-20
<br>Cover Display Date: 20 December 2018
<br>DOI: 10.23919/INCIT.2018.8584871
<br>Description: One well known and long-lasting problem in the video tracking is that one particular algorithm would perform well on a certain environmental characteristic. Whenever the characteristic in the scene changes, the performance of the algorithm affected. This research proposes a multiagent-based for video tracking system. The agents follow the odd-man out strategy, which odd agents will be credited less than the favorite ones. We tested our algorithm against two tough videos. The results show that our approach yield satisfactory outcomes. The final tracking results are always within the boundary of the groundtruth, given that there are two out of five correct results.
<br>Citations: 0
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: A Crowd Simulation in Large Space Urban
<br>Cover Date: 2018-12-20
<br>Cover Display Date: 20 December 2018
<br>DOI: 10.23919/INCIT.2018.8584878
<br>Description: We present a multiagent-based framework for crowd simulation in large space urban area on a standalone PC. We use Belief-Desire-Intention (BDI) for modeling individual agent behavior. We use RVO for handling a large number of agents. The simulation engine is Unity3d which also take care of the visualization. We experimented our framework with up to 20,000 agents, navigating them from origins to destinations. We found that we can navigate agents successfully. The execution time increases when the number of agent increase. The visualization becomes slow when the number of agent is higher than 1000 agents. We found that the the simulation steps also increases when the number of agent is not higher than 5005.
<br>Citations: 7
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: Fair Payoffs Distribution in Linear Production Game by Shapley Value
<br>Cover Date: 2018-12-20
<br>Cover Display Date: 20 December 2018
<br>DOI: 10.23919/INCIT.2018.8584872
<br>Description: Shapley value is regarded as a fair payoff distribution concept for cooperative agents. While traditional cooperative game assume superadditivity and non-externalty, real world environments do not hold this assumption. We show that in linear production game, the environment is non-superadditive is with externalties. In such environment, grand coalition does not provide optimal solution to the system. Consequently, applying traditional shapley value does not provide an attractive payoff to agents. In addition, fairness may also be lost because individual payoffs are less than singleton coalition values. We show how this environments may occur and how we can propose a more attractive and, still, fair payoffs to agents.
<br>Citations: 1
<br>Aggregation Type: Conference Proceeding
<br>-------------------
<br><br><br>Title: Fair payoff distribution in multiagent systems under Pareto optimality
<br>Cover Date: 2017-07-01
<br>Cover Display Date: 1 July 2017
<br>DOI: 10.1109/INCIT.2017.8257861
<br>Description: This research proposes a set of algorithms to compute fair payoff distribution among agents in service composition domain based on their contribution. In our system, intelligent agents, representing service providers, negotiate among themselves and form composite services to satisfy multiple-objective requirements. The quality of service for each objective is measured in term of degree of satisfaction. The overall quality of service is achieved by maximizing requesters satisfaction on all objectives according to Pareto optimality. We then deploy Shapley Value concept for fair payoff distribution among agents based on their contributions to the requesters optimal satisfaction. Since the computational complexity for Shapley Value is exponential, we are interested in investigating how well the algorithms for computing payoff perform. We found that on a typical computer, the algorithm can cope with around 20 agents with reasonable computational time.
<br>Citations: 0
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: An anytime algorithm for scheduling tasks for multiagent systems
<br>Cover Date: 2017-01-01
<br>Cover Display Date: 2017
<br>DOI: 10.1007/978-3-319-69456-6_29
<br>Description: This research proposes an any time algorithm for a task scheduling problem among agents. The tasks are composed of atomic tasks and are to be distributed to coalitions of agents as subtasks for parallel execution. We model the problem and propose an algorithm for it. The algorithm calls other low level algorithms to recursively generate plans for agents. The results show satisfactory results that the convergent times are reasonably short and are close to termination time in many settings. We also found that the distribution of input values affect the performance of the algorithm similar to the optimal coalition structure problem.
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: A light-weighted multiagent-based crowd simulation
<br>Cover Date: 2016-03-21
<br>Cover Display Date: 21 March 2016
<br>DOI: 10.1109/ACDT.2016.7437651
<br>Description: The main contributions of this research include developing a light-weighted multiagent-based system for crowd simulation and modeling bounded rationality of the agents in such system. We deploy the belief-desire-intention (BDI) concept to model our agents. Whereas most works in the field assume perfect information, we take into account the bounded rationality characteristics of human beings into the perception of agents. We found that the increasing number of agents affects the performance by increasing duration, number of rounds, duration per round, duration per agent, and round per agent in two dense scenes. However, the perception process added on does not directly affect the performance of the algorithm. With regards to the behavior of the agents, we found that most agents are affected by the increasing number of agents that their paths divert significantly from the original plan. However, there are some agents which apparently can maintain their paths close to their original ones.
<br>Citations: 1
<br>Aggregation Type: Conference Proceeding
<br>-------------------
<br><br><br>Title: Multi-disciplinary trends in artificial intelligence: 10th international workshop, MIWAI 2016 Chiang Mai, Thailand, december 7-9, 2016 proceedings
<br>Cover Date: 2016-01-01
<br>Cover Display Date: 2016
<br>DOI: N/A
<br>Description: N/A
<br>Citations: 0
<br>Aggregation Type: Book Series
<br>-------------------
<br><br><br>Title: Preface
<br>Cover Date: 2016-01-01
<br>Cover Display Date: 2016
<br>DOI: N/A
<br>Description: N/A
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: Design and development of a hull stabilization system for personnel carrier
<br>Cover Date: 2015-05-21
<br>Cover Display Date: 21 May 2015
<br>DOI: 10.1109/ACDT.2015.7111601
<br>Description: This paper presents a design and development of a hull stabilization system for personal carrier. A Sliding Mode Controller (SMC) was employed to control roll angle of the carrier, which is the most critical degree-of-freedom (DOF) to stabilize the carrier. Simulation results show good performance of the proposed controller, which can bring the roll angle to the setpoint quickly with a critical damp response. A comparison between open-loop and SMC was also conducted, the result of which ensures the effectiveness of the algorithm. A carrier testbed equipped with a digital gyroscope as the attitude sensor and trolling motors as the actuator, was constructed to test and validate the possibility and performance of the propose stabilization system.
<br>Citations: 1
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: A Load Balancing in Task Allocation of a Multiagent System
<br>Cover Date: 2014-01-01
<br>Cover Display Date: 2014
<br>DOI: 10.1109/ISCBI.2014.32
<br>Description: Task allocation is an important area of research in multiagent systems because it can efficiently solve complex problems in the real world. Such a problem is power grid systems, where agents, representing power plants, are given the task to provide consistent supply to consumers, whose needs vary over the time. They need to jointly plan in order to find appropriate supply schedules over the course of time. This research i) formulates a new task allocation problem, which provide stable supply, and ii) proposes an algorithmic approach to find (near) optimal plan. The results show that, out of 18 data distribution, the convergence times are high when the means of the data is low and vice versa.
<br>Citations: 0
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface
<br>Cover Date: 2013-12-01
<br>Cover Display Date: 2013
<br>DOI: 10.1007/978-3-642-44949-9
<br>Description: N/A
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: Towards optimal service composition upon QoS in agent cooperation
<br>Cover Date: 2013-01-01
<br>Cover Display Date: 2013
<br>DOI: 10.1504/IJCSE.2013.053063
<br>Description: It is quite common in tourism industry that a tourist would love to gain the most wonderful experience from visiting multiple places in one trip. This is a service composition problem and is difficult to manage because of several reasons. We address this problem by proposing an agent-based service composition framework to allocate to the tourist an optimal composite service. We take into account a number of factors including: 1) all the places of interest must be visited; 2) the preference on visiting places must be obeyed; 3) the total price is within the budget; 4) the time constraint must be obeyed; 5) the payoffs for service providers are worthwhile and fair. We propose a bottom-up approach to allocate the optimal service composition where intelligent agents are deployed to provide flexibility and efficiency to the system. As a result, the system is more independent and every party is better off. Copyright © 2013 Inderscience Enterprises Ltd.
<br>Citations: 6
<br>Aggregation Type: Journal
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<br><br><br>Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface
<br>Cover Date: 2012-12-01
<br>Cover Display Date: 2012
<br>DOI: 10.1007/978-3-642-35455-7
<br>Description: N/A
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: A General Family of Preferential Belief Removal Operators
<br>Cover Date: 2012-08-01
<br>Cover Display Date: August 2012
<br>DOI: 10.1007/s10992-012-9235-5
<br>Description: Most belief change operators in the AGM tradition assume an underlying plausibility ordering over the possible worlds which is transitive and complete. A unifying structure for these operators, based on supplementing the plausibility ordering with a second, guiding, relation over the worlds was presented in Booth et al. (Artif Intell 174:1339-1368, 2010). However it is not always reasonable to assume completeness of the underlying ordering. In this paper we generalise the structure of Booth et al. (Artif Intell 174:1339-1368, 2010) to allow incomparabilities between worlds. We axiomatise the resulting class of belief removal functions, and show that it includes an important family of removal functions based on finite prioritised belief bases. © 2012 Springer Science+Business Media B.V.
<br>Citations: 0
<br>Aggregation Type: Journal
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<br><br><br>Title: Optimal service composition via agent-based quality of service
<br>Cover Date: 2011-12-26
<br>Cover Display Date: 2011
<br>DOI: 10.1007/978-3-642-25725-4_24
<br>Description: Optimal service allocation has gained a lot of attention from researchers recently. We address this problem by proposing an agent-based composite web-services framework to allocate to the tourist an optimal service composition, one which maximally satisfies the tourist. By saying optimal service composition, we take into account a number of factors including i) the number of visited places must be maximal, ii) the number of redundant places must be minimal, iii) the total price is within the budget, and iv) the time constraint must be obeyed. We propose an approach to allow service requesters for choosing the optimal service. Our architecture deploys agents in order to provide flexibility and efficiency to the system. © 2011 Springer-Verlag.
<br>Citations: 1
<br>Aggregation Type: Book Series
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<br><br><br>Title: Automatic composition and mediation on multiple-language semantic web services
<br>Cover Date: 2011-12-26
<br>Cover Display Date: 2011
<br>DOI: 10.1007/978-3-642-25725-4_5
<br>Description: Web services have been attracting many attentions in both research and industry communities due to their potential of being invoked automatically based on users requests. In order to make this potential practical, there are two tasks needed to be fulfilled including (i) automatic discovery and composition of appropriate services and (ii) automatic invocation of sequenced services to achieve the desired goal. However, the lack of a mechanism of semantic representation in typical services descriptions has hindered this vision significantly. The recently introduced Semantic Web services are promising to overcome this obstacle by employing ontologies to describe the service operations, therefore the semantics of the provided services can be understood and reasoned automatically by computer programs. Nevertheless, since the standard for ontological knowledge representation over the Semantic Web services has not been completely established yet, there are many description languages have been introduced. Automatic composition and mediation of multiple-language Semantic Web services thus become a challenging issue. In this paper we introduce an approach to tackle this problem. Based on extended plug-in technique for service discovery, we develop a framework for composition of multiple services and make use of concept similarity evaluated over ontological concepts to handle the problem of multiple service description languages. We also discuss automatic mediation of multiple services to have the involved services automatically invoked necessarily. To show the practical aspect of our approach, we have applied the composition framework on the most two popular description languages, namely OWL-S and WSMO. The initial results showed that our approach has achieved reasonable performance in terms of accuracy. © 2011 Springer-Verlag.
<br>Citations: 2
<br>Aggregation Type: Book Series
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<br><br><br>Title: Learning conditionally lexicographic preference relations
<br>Cover Date: 2011-12-01
<br>Cover Display Date: 2011
<br>DOI: N/A
<br>Description: N/A
<br>Citations: 1
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: Computing optimal coalition structures in non-linear logistics domains
<br>Cover Date: 2011-01-01
<br>Cover Display Date: October 2011
<br>DOI: 10.1504/IJIIDS.2011.043127
<br>Description: We study computing optimal coalition structures in non-linear logistics domains, where coalition values are not known a priori and computing them is NP-hard. In our setting, the common goal of the agents is to minimise the system's cost. Agents perform two steps: 1 deliberate appropriate coalitions 2 exchange computed coalitions and generate coalition structures. We apply the concept of best coalition introduced in Sombattheera and Ghose (2008), to work in the non-linear logistics domains. We provide an algorithm and explain via examples to show how it works. Lastly, we show the empirical results of our algorithm in terms of elapsed time and number of coalition structures generated. Copyright © 2011 Inderscience Enterprises Ltd.
<br>Citations: 0
<br>Aggregation Type: Journal
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<br><br><br>Title: Preface
<br>Cover Date: 2011-01-01
<br>Cover Display Date: 2011
<br>DOI: N/A
<br>Description: N/A
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: Conviviality measures
<br>Cover Date: 2011-01-01
<br>Cover Display Date: 2011
<br>DOI: N/A
<br>Description: Conviviality has been introduced as a social science concept for multiagent systems to highlight soft qualitative requirements like user friendliness of systems. In this paper we introduce formal conviviality measures for dependence networks using a coalitional game theoretic framework, which we contrast with more traditional efficiency and stability measures. Roughly, more opportunities to work with other people increases the conviviality, whereas larger coalitions may decrease the efficiency or stability of these involved coalitions. We first introduce assumptions and requirements, then we introduce a classification, and finally we introduce the conviviality measures. We use a running example from robotics to illustrate the measures. Copyright © 2011, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
<br>Citations: 12
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: Quality indicators in requirements elicitation
<br>Cover Date: 2010-12-01
<br>Cover Display Date: 2010
<br>DOI: N/A
<br>Description: Domain knowledge is found to be a crucial factor in attaining quality of requirements. System analysts, who have adequate knowledge of software often don't usually understand the organizational context well. This paper, presents a novel approach that utilizes the Tropos, Software System-Business Model (SS-BM) to requirements list elicitation. In the proposed method, requirements items are mapped to SS-BM elements based on their semantic meanings. The mapped requirements list and SS-BM are analyzed in specific sequence according to multiple checking points. Problems with the requirements list are identified in the analysis process and possible improvements are proposed. Quality indicators are used to summarize the quality of requirements at the end of the elicitation process.
<br>Citations: 0
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: An algorithm for computing optimal coalition structures in non-linear logistics domains
<br>Cover Date: 2010-09-17
<br>Cover Display Date: 2010
<br>DOI: 10.1007/978-3-642-12101-2_9
<br>Description: We study computing optimal coalition structures in non-linear logistics domains where coalition values are not known a priori and computing them is NP-Hard problem. The common goal of the agents is to minimize the system's cost. Agents perform two steps: i) deliberate appropriate coalitions, and ii) exchange computed coalitions and generate coalition structures. We apply the concept of best coalition introduced in [1], to work in the non-linear logistics domain. We provide an algorithm, explain via examples to show it works. Lastly, we show the empirical results of our algorithm in terms of elapsed time and number of coalition structures generated. © 2010 Springer-Verlag Berlin Heidelberg.
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: Learning conditionally lexicographic preference relations
<br>Cover Date: 2010-01-01
<br>Cover Display Date: 2010
<br>DOI: 10.3233/978-1-60750-606-5-269
<br>Description: We consider the problem of learning a user's ordinal preferences on a multiattribute domain, assuming that her preferences are lexicographic. We introduce a general graphical representation called LP-trees which captures various natural classes of such preference relations, depending on whether the importance order between attributes and/or the local preferences on the domain of each attribute is conditional on the values of other attributes. For each class we determine the Vapnik-Chernovenkis dimension, the communication complexity of preference elicitation, and the complexity of identifying a model in the class consistent with a set of user-provided examples. © 2010 The authors and IOS Press. All rights reserved.
<br>Citations: 69
<br>Aggregation Type: Book Series
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<br><br><br>Title: A general family of preferential belief removal operators
<br>Cover Date: 2009-12-01
<br>Cover Display Date: 2009
<br>DOI: 10.1007/978-3-642-04893-7_4
<br>Description: Most belief change operators in the AGM tradition assume an underlying plausibility ordering over the possible worlds which is transitive and complete. A unifying structure for these operators, based on supplementing the plausibility ordering with a second, guiding, relation over the worlds was presented in [5]. However it is not always reasonable to assume completeness of the underlying ordering. In this paper we generalise the structure of [5] to allow incomparabilities between worlds. We axiomatise the resulting class of belief removal functions, and show that it includes an important family of removal functions based on finite prioritised belief bases. © Springer-Verlag 2009.
<br>Citations: 1
<br>Aggregation Type: Book Series
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<br><br><br>Title: A best-first anytime algorithm for computing optimal coalition structures
<br>Cover Date: 2008-01-01
<br>Cover Display Date: 2008
<br>DOI: N/A
<br>Description: This work presents a best-first anytime algorithm for computing optimal coalition structures. The approach is novel in that it generates coalition structures based on coalition values, while existing algorithms base their generation on the structure (members and configurations) of coalitions. With our algorithm, coalition structures are generated by repeatedly choosing the best coalition, as determined using a novel metric called agent's contribution to coalition structure that we define. We have compared the performance of our algorithm against that of Rahwan et al [5] using 20 data distributions. Our results show that our algorithm almost always converges on an optimal coalition structure faster (although it terminates later in some cases). Empirically, our algorithm almost always yields better than or as good as Rahwan et al's results at any point in time. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
<br>Citations: 12
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: A distributed algorithm for coalition formation in linear production domain
<br>Cover Date: 2006-12-01
<br>Cover Display Date: 2006
<br>DOI: N/A
<br>Description: Coalition formation is an important area of research in multi-agent systems. The large number of agents can make coalition formation become a complex process. The problem of dealing with large number of agents during coalition formation has received little attention in the literature. Previous studies assume that each coalition value is known a priori. This assumption is impractical in realworld settings. Furthermore, the problem of finding coalition values become intractable for even a relatively small number of agents. This work studies coalition formation among fully cooperative agents in linear production domain, where each coalition value is not known a priori. The common goal of the agents is to maximize the system's profit. We propose a distributed algorithm that allow agents to i) deliberate profitable coalitions, and ii) compute optimal coalition structure. We show that our algorithm outperforms exhaustive search when generating profitable coalitions, which can be used to achieve optimal coalition structure that yields the system's maximal profit.
<br>Citations: 2
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: A pruning-based algorithm for computing optimal coalition structures in linear production domains
<br>Cover Date: 2006-01-01
<br>Cover Display Date: 2006
<br>DOI: 10.1007/11766247_2
<br>Description: Computing optimal coalition structures is an important research problem in multi-agent systems. It has rich application in real world problems, including logistics and supply chains. We study computing optimal coalition structures in linear production domains. The common goal of the agents is to maximize the system's profit. Agents perform two steps: i) deliberate profitable coalitions, and ii) exchange computed coalitions and generate coalition structures. In our previous studies, agents keep growing their coalitions from the singleton ones in the deliberation step. This work takes opposite approach that agents keep pruning unlikely profitable coalitions from the grand coalition. It also relaxes the strict condition of coalition center, which yields the minimal cost to the coalition. Here, agents merely keep generating profitable coalitions. Furthermore, we introduce new concepts, i.e., beat coalitions and pattern, in our algorithm and provide an example of how it can work. Lastly, we show that our algorithm outperforms exhaustive search in generating optimal coalition structures in terms of elapsed time and number of coalition structures generated. © Springer-Verlag Berlin Heidelberg 2006.
<br>Citations: 5
<br>Aggregation Type: Book Series
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<br><br><br>Title: Supporting dynamic supply networks with agent-based coalitions
<br>Cover Date: 2006-01-01
<br>Cover Display Date: 2006
<br>DOI: 10.1007/11779568_120
<br>Description: This work extends our previous work to offer richer support for collaboration across supply networks. The role of agents are divided into three sectors at any point In time: buyers, sellers and LPs. Agents take two steps to form coalitions: i) agents in each sector sequencially form primary coalitions in order to increase bargaining power, selling capacity or service efficiency, and ii) agents form secondary coalitions across sectors In order to finalize the deal and deliver goods to buyers. We propose a negotiation protocol and deliberation mechanism. The negotiation protocol allows thorough communication among agents within and across sectors. The deliberation mechanism allows agents to consider potential coalition members and attractive payoffs for them. We provide examples of how they can help agents form coalitions successfully. © Springer-Verlag Berlin Heidelberg 2006.
<br>Citations: 0
<br>Aggregation Type: Book Series
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<br><br><br>Title: A distributed branch-and-bound algorithm for computing optimal coalition structures
<br>Cover Date: 2006-01-01
<br>Cover Display Date: 2006
<br>DOI: 10.1007/11752912_34
<br>Description: Coalition formation is an important area of research in multiagent systems. Computing optimal coalition structures for a large number of agents is an important problem in coalition formation but has received little attention in the literature. Previous studies assume that each coalition value is known a priori. This assumption is impractical in real world settings. Furthermore, the problem of finding coalition values become intractable for even a relatively small number of agents. This work proposes a distributed branch-and-bound algorithm for computing optimal coalition structures in linear production domain, where each coalition value is not known a priori. The common goal of the agents is to maximize the system's profit. In our algorithm, agents perform two tasks: i) deliberate profitable coalitions, and ii) cooperatively compute optimal coalition structures. We show that our algorithm outperforms exhaustive search in generating optimal coalition structure in terms of elapses time and number of coalition structures generated. © Springer-Verlag Berlin Heidelberg 2006.
<br>Citations: 3
<br>Aggregation Type: Book Series
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<br><br><br>Title: Agent-based prototyping of web-based systems
<br>Cover Date: 2006-01-01
<br>Cover Display Date: 2006
<br>DOI: 10.1007/11779568_84
<br>Description: Agent-oriented conceptual modelling In notations such as the i* framework [13] have gained considerable currency in the recent past Such notations model organizational context and offer high-level social/ anthropomorphic abstractions (such as goals, tasks, softgoals and dependencies) as modelling constructs. It has been argued that such notations help answer questions such as what goals exist, how key actors depend on each other and what alternatives must be considered. Our contribution in this paper it to show an approach to executing high-level requirements models represented in the i* agent-oriented conceptual modelling language. We achieve this by translating these models into sets of interacting agents implemented in the 3APL language. This approach enables us to analyze early phase system models by performing rule-/consistency-checking at higher-levels of abstraction. We show how this approach finds special application in the analysis of high-level models of a web-based system. © Springer-Verlag Balin Heidelberg 2006.
<br>Citations: 4
<br>Aggregation Type: Book Series
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<br><br><br>Title: Agent-based coalitions in dynamic supply chains
<br>Cover Date: 2005-12-01
<br>Cover Display Date: 2005
<br>DOI: N/A
<br>Description: Coalition formation is an important issue in multi-agent systems. Recent work in the area has focused on reducing the complexity of forming coalitions, i.e., each agent deliberately searches for potential coalition members before negotiating with them. We propose a framework for coalition formation of agents in a dynamic supply chain environment. The framework is composed of a negotiation protocol and a decision mechanism. The negotiation protocol allows thorough communication among agents across sectors (buyers, sellers, logistic providers). With the decision mechanism, agents take two steps to form coalitions: i) agents in each sector form loosely-coupled coalitions in order to decrease the complexity of the negotiation, and ii) agents form coalitions across sectors in order to deliver goods to end customers. We provide an example of how they can help agents form coalitions successfully.
<br>Citations: 3
<br>Aggregation Type: Conference Proceeding
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<br><br><br>Title: Dynamic coalition in agent aware adhoc virtual P2P interconnect grid computing system - A3Pvigrid
<br>Cover Date: 2005-12-01
<br>Cover Display Date: 2005
<br>DOI: N/A
<br>Description: Artificial Intelligence and High performance Grid computing systems are two different fields of technologies that have been much researched upon and are as old as the development of personal computers and its related technologies. Technologies such as Agent based systems and the Semantic Grid have evolved with the use of Artificially Intelligent techniques such as the Turing system of intelligence measurement. Similarly Peer to Peer computing and Supercomputing Grids have evolved from distributed and middleware clustering systems such as Condor. In this paper a new architectural schematic is proposed where technologies such as Agents, P2P computing and Adhoc systems are incorporated in a Grid Computing framework for the optimal Job processing and delivery to the end user transparently. Applying Dynamic Coalition techniques in Agent based Grid computing systems has been a meagrely researched Area. The proposed system A3pviGrid tends to deploy a service oriented schematic that enables users to search for, negotiate using agents, do remote Job Processing and use resources without the need for a resource discovery model in place that is commonly used in current day high performance Grid systems.
<br>Citations: 2
<br>Aggregation Type: Conference Proceeding
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