Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010
Virtual organizations are conceived as an eective mecha- nism for ensuring coordination and globa... more Virtual organizations are conceived as an eective mecha- nism for ensuring coordination and global goal fullment of an open system, in which heterogeneous entities (agents or services) interact and might also present self-interested behaviours. Organizations describe the system functionality, structure and dynamics. However, available tools rarely give support for these organizational abstractions. The THOMAS multi-agent architecture allows the development of open multi-agent ap- plications. It provides a useful framework for the development of virtual organizations, on the basis of a service-based approach. In this paper, the Organization Management System component of the THOMAS architec- ture is presented. The Organization Management System is in charge of the organization life-cycle process, including the normative management. It provides a set of structural, informative and dynamic services, which allow describing both specication and administration features of the structural elements of the organization and their dynamics. Moreover, it makes use of a normative language for controlling the service request, provision and register. In this paper, the Organization Management Sys- tem and its implementation are detailed.
... means between conflicting desires (Amgoud, 2003) and objectives (Amgoud & Kaci, 2004), as... more ... means between conflicting desires (Amgoud, 2003) and objectives (Amgoud & Kaci, 2004), as a qualitative means of reasoning about the expected value of the realization of certain actions (Fox & Parsons, 1998) and as generator of plans (Hulstijn & van der Torre, 2004; Simari ...
Today, real-time systems should be designed to be flexible and adaptable. For this reason, the mu... more Today, real-time systems should be designed to be flexible and adaptable. For this reason, the multi-agent system paradigm seems to be appropriate for real-time system development. In the case of distributed real-time systems, complexity is added when a node must delegate a task with temporal restrictions to another node. This delegation can be modeled as a commitment act in a
The Migration Process is a phenomenon that includes a variety of actors, societies and political ... more The Migration Process is a phenomenon that includes a variety of actors, societies and political issues at different levels. In the migration problem it is then possible to observe complex interactions among different entities: there are links among economics, politics, social, commercial, labour, health, culture, and safety areas. Migration movements may also influence and be influenced by the effects of policies and norms of both sending and receiving countries. One of the key factors that influence the Migration Process behavior is the Labour Market, which is simultaneously affected by Financial Markets. These interactions have been traditionally represented by mathematical approaches that do not allow including flexibility, autonomy, adaptive and pro-activity features that are present into the dynamic and complex real life migration scenarios. On the other hand, the Multiagent System (MAS) paradigm has been successfully applied in studies related to mass movement in complex environments. In this paper a MAS simulation approach is proposed to simulate the migration process and to model micro-level interaction protocols that link Labour and Financial Markets to Migration Processes (MP-LM&FM) in order to observe dynamic behaviours that may emerge at macro level.
Recommender systems are capable of providing users with personalized information that is adjusted... more Recommender systems are capable of providing users with personalized information that is adjusted to their needs. One particular case of these systems is applied to the tourism industry. Tourism recommender systems offer services such
as hotel reservation, restaurant reservation, and visit plans personalized for each tourist. The Social-Net Tourism Recommender System is a tourism recommender
system that is based on agent technology and uses social networks as its basis for recommendations. Nevertheless, these systems face some problems. On the one hand information needs to be mantained up-to-date, which can result in a costly task if not performed automatically. On the other hand, it may be interesting to include third parties services in the recommendation since they improve the quality of the recommendations. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing
techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third parties services that are not offered by service providers inside the system.
Recommender systems face some problems. On the one hand information needs to be maintained update... more Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.
An agent-based negotiation team is a group of two or more agents with their own and possibly con... more An agent-based negotiation team is a group of two or more agents with their own and possibly conflicting preferences who join together as a single negotiating party because they share a common goal which is related to the negotiation. Scenarios involving negotiation teams require coordination among party members in order to reach a good agreement for all of the party members. An intra-team strategy defines what decisions are taken by the negotiation team and when and how these decisions are taken. Thus, they are tightly linked with the results obtained by the team in a negotiation process. Environmental conditions affect the performance of the different intra-team strategies in different ways. Thus, team members need to analyze their environment in order to select the most appropriate strategy according to the current conditions. In this paper, we analyze how environmental conditions affect different intra-team strategies in order to provide teams with the knowledge necessary to select the proper intra-team strategy.
Agent-based negotiation teams are groups of two or more interdependent agents with their own and ... more Agent-based negotiation teams are groups of two or more interdependent agents with their own and possibly conflicting goals that join together as a single negotiating party because they share a common goal that is related to the negotiation. In this paper we present a general workflow of tasks for agents that participate in a negotiation team. Furthermore, we focus on the study of intra-team organizations, which define the roles played by team members, what decisions are taken by the team, and how and when they are taken, and the negotiation strategy carried out with the opponent. The performance of the proposed organizations is tested in environmental scenarios where team diversity is different.
IEEE Transactions on Systems, Man, and Cybernetics, 2012
In this article, an agent-based negotiation model
for negotiation teams that negotiate a deal wi... more In this article, an agent-based negotiation model
for negotiation teams that negotiate a deal with an opponent
is presented. Agent-based negotiation teams are groups of agents that join together as a single negotiation party because they share an interest that is related to the negotiation process. The model relies on a trusted mediator that coordinates and helps team members in the decisions that they have to take during the negotiation process: which offer is sent to the opponent, and whether or not the offers received from the opponent are accepted. The main strength of the proposed negotiation model is the fact that it guarantees unanimity within team decisions since decisions report a utility to team members that is greater than or equal to their aspiration levels at each negotiation round.
This work analyzes how unanimous decisions are taken within
the team and the robustness of the model against different types of manipulations. An empirical evaluation is also performed to study the impact of the different parameters of the model.
In this article we study the impact of the negotiation environment on the performance of several ... more In this article we study the impact of the negotiation environment on the performance of several intra-team strategies (team dynamics) for agent-based negotiation teams that negotiate with an opponent. An agent-based negotiation team is a group of agents that joins together as a party because they share common interests in the negotiation at hand. It is experimentally shown how negotiation environment conditions like the deadline of both parties, the concession speed of the opponent, similarity among team members, and team size affect performance metrics like the minimum utility of team members, the average utility of team members, and the number of negotiation rounds. Our goal is identifying which intra-team strategies work better in different environmental conditions in order to provide useful knowledge for team members to select appropriate intra-team strategies according to environmental conditions.
Engineering Applications of Artificial Intelligence, 2013
An agent-based negotiation team is a group of interdependent agents that join together as a singl... more An agent-based negotiation team is a group of interdependent agents that join together as a single negotiation party due to their shared interests in the negotiation at hand. The reasons to employ an agent-based negotiation team may vary: (i) more computation and parallelization capabilities; (ii) unite agents with different expertise and skills whose joint work makes it possible to tackle complex negotiation domains; (iii) the necessity to represent different stakeholders or different preferences in the same party (e.g., organizations, countries, married couple, etc.). The topic of agent-based negotiation teams has been recently introduced in multi-agent research. Therefore, it is necessary to identify good practices, challenges, and related research that may help in advancing the state-of-the-art in agent-based negotiation teams. For that reason, in this article we review the tasks to be carried out by agent-based negotiation teams. Each task is analyzed and related with current advances in different research areas. The analysis aims to identify special challenges that may arise due to the particularities of agent-based negotiation teams.
A negotiation team is a set of agents with common and possibly also conflicting preferences that ... more A negotiation team is a set of agents with common and possibly also conflicting preferences that forms one of the parties of a negotiation. A negotiation team is involved in two decision making processes simultaneously, a negotiation with the opponents, and an intra-team process to decide on the moves to make in the negotiation. This article focuses on negotiation team decision making for circumstances that require unanimity of team decisions. Existing agent-based approaches only guarantee unanimity in teams negotiating in domains exclusively composed of predictable and compatible issues. This article presents a model for negotiation teams that guarantees unanimous team decisions in domains consisting of predictable and compatible, and also unpredictable issues. Moreover, the article explores the influence of using opponent, and team member models in the proposing strategies that team members use. Experimental results show that the team benefits if team members employ Bayesian learning to model their teammates' preferences.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010
Virtual organizations are conceived as an eective mecha- nism for ensuring coordination and globa... more Virtual organizations are conceived as an eective mecha- nism for ensuring coordination and global goal fullment of an open system, in which heterogeneous entities (agents or services) interact and might also present self-interested behaviours. Organizations describe the system functionality, structure and dynamics. However, available tools rarely give support for these organizational abstractions. The THOMAS multi-agent architecture allows the development of open multi-agent ap- plications. It provides a useful framework for the development of virtual organizations, on the basis of a service-based approach. In this paper, the Organization Management System component of the THOMAS architec- ture is presented. The Organization Management System is in charge of the organization life-cycle process, including the normative management. It provides a set of structural, informative and dynamic services, which allow describing both specication and administration features of the structural elements of the organization and their dynamics. Moreover, it makes use of a normative language for controlling the service request, provision and register. In this paper, the Organization Management Sys- tem and its implementation are detailed.
... means between conflicting desires (Amgoud, 2003) and objectives (Amgoud & Kaci, 2004), as... more ... means between conflicting desires (Amgoud, 2003) and objectives (Amgoud & Kaci, 2004), as a qualitative means of reasoning about the expected value of the realization of certain actions (Fox & Parsons, 1998) and as generator of plans (Hulstijn & van der Torre, 2004; Simari ...
Today, real-time systems should be designed to be flexible and adaptable. For this reason, the mu... more Today, real-time systems should be designed to be flexible and adaptable. For this reason, the multi-agent system paradigm seems to be appropriate for real-time system development. In the case of distributed real-time systems, complexity is added when a node must delegate a task with temporal restrictions to another node. This delegation can be modeled as a commitment act in a
The Migration Process is a phenomenon that includes a variety of actors, societies and political ... more The Migration Process is a phenomenon that includes a variety of actors, societies and political issues at different levels. In the migration problem it is then possible to observe complex interactions among different entities: there are links among economics, politics, social, commercial, labour, health, culture, and safety areas. Migration movements may also influence and be influenced by the effects of policies and norms of both sending and receiving countries. One of the key factors that influence the Migration Process behavior is the Labour Market, which is simultaneously affected by Financial Markets. These interactions have been traditionally represented by mathematical approaches that do not allow including flexibility, autonomy, adaptive and pro-activity features that are present into the dynamic and complex real life migration scenarios. On the other hand, the Multiagent System (MAS) paradigm has been successfully applied in studies related to mass movement in complex environments. In this paper a MAS simulation approach is proposed to simulate the migration process and to model micro-level interaction protocols that link Labour and Financial Markets to Migration Processes (MP-LM&FM) in order to observe dynamic behaviours that may emerge at macro level.
Recommender systems are capable of providing users with personalized information that is adjusted... more Recommender systems are capable of providing users with personalized information that is adjusted to their needs. One particular case of these systems is applied to the tourism industry. Tourism recommender systems offer services such
as hotel reservation, restaurant reservation, and visit plans personalized for each tourist. The Social-Net Tourism Recommender System is a tourism recommender
system that is based on agent technology and uses social networks as its basis for recommendations. Nevertheless, these systems face some problems. On the one hand information needs to be mantained up-to-date, which can result in a costly task if not performed automatically. On the other hand, it may be interesting to include third parties services in the recommendation since they improve the quality of the recommendations. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing
techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third parties services that are not offered by service providers inside the system.
Recommender systems face some problems. On the one hand information needs to be maintained update... more Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.
An agent-based negotiation team is a group of two or more agents with their own and possibly con... more An agent-based negotiation team is a group of two or more agents with their own and possibly conflicting preferences who join together as a single negotiating party because they share a common goal which is related to the negotiation. Scenarios involving negotiation teams require coordination among party members in order to reach a good agreement for all of the party members. An intra-team strategy defines what decisions are taken by the negotiation team and when and how these decisions are taken. Thus, they are tightly linked with the results obtained by the team in a negotiation process. Environmental conditions affect the performance of the different intra-team strategies in different ways. Thus, team members need to analyze their environment in order to select the most appropriate strategy according to the current conditions. In this paper, we analyze how environmental conditions affect different intra-team strategies in order to provide teams with the knowledge necessary to select the proper intra-team strategy.
Agent-based negotiation teams are groups of two or more interdependent agents with their own and ... more Agent-based negotiation teams are groups of two or more interdependent agents with their own and possibly conflicting goals that join together as a single negotiating party because they share a common goal that is related to the negotiation. In this paper we present a general workflow of tasks for agents that participate in a negotiation team. Furthermore, we focus on the study of intra-team organizations, which define the roles played by team members, what decisions are taken by the team, and how and when they are taken, and the negotiation strategy carried out with the opponent. The performance of the proposed organizations is tested in environmental scenarios where team diversity is different.
IEEE Transactions on Systems, Man, and Cybernetics, 2012
In this article, an agent-based negotiation model
for negotiation teams that negotiate a deal wi... more In this article, an agent-based negotiation model
for negotiation teams that negotiate a deal with an opponent
is presented. Agent-based negotiation teams are groups of agents that join together as a single negotiation party because they share an interest that is related to the negotiation process. The model relies on a trusted mediator that coordinates and helps team members in the decisions that they have to take during the negotiation process: which offer is sent to the opponent, and whether or not the offers received from the opponent are accepted. The main strength of the proposed negotiation model is the fact that it guarantees unanimity within team decisions since decisions report a utility to team members that is greater than or equal to their aspiration levels at each negotiation round.
This work analyzes how unanimous decisions are taken within
the team and the robustness of the model against different types of manipulations. An empirical evaluation is also performed to study the impact of the different parameters of the model.
In this article we study the impact of the negotiation environment on the performance of several ... more In this article we study the impact of the negotiation environment on the performance of several intra-team strategies (team dynamics) for agent-based negotiation teams that negotiate with an opponent. An agent-based negotiation team is a group of agents that joins together as a party because they share common interests in the negotiation at hand. It is experimentally shown how negotiation environment conditions like the deadline of both parties, the concession speed of the opponent, similarity among team members, and team size affect performance metrics like the minimum utility of team members, the average utility of team members, and the number of negotiation rounds. Our goal is identifying which intra-team strategies work better in different environmental conditions in order to provide useful knowledge for team members to select appropriate intra-team strategies according to environmental conditions.
Engineering Applications of Artificial Intelligence, 2013
An agent-based negotiation team is a group of interdependent agents that join together as a singl... more An agent-based negotiation team is a group of interdependent agents that join together as a single negotiation party due to their shared interests in the negotiation at hand. The reasons to employ an agent-based negotiation team may vary: (i) more computation and parallelization capabilities; (ii) unite agents with different expertise and skills whose joint work makes it possible to tackle complex negotiation domains; (iii) the necessity to represent different stakeholders or different preferences in the same party (e.g., organizations, countries, married couple, etc.). The topic of agent-based negotiation teams has been recently introduced in multi-agent research. Therefore, it is necessary to identify good practices, challenges, and related research that may help in advancing the state-of-the-art in agent-based negotiation teams. For that reason, in this article we review the tasks to be carried out by agent-based negotiation teams. Each task is analyzed and related with current advances in different research areas. The analysis aims to identify special challenges that may arise due to the particularities of agent-based negotiation teams.
A negotiation team is a set of agents with common and possibly also conflicting preferences that ... more A negotiation team is a set of agents with common and possibly also conflicting preferences that forms one of the parties of a negotiation. A negotiation team is involved in two decision making processes simultaneously, a negotiation with the opponents, and an intra-team process to decide on the moves to make in the negotiation. This article focuses on negotiation team decision making for circumstances that require unanimity of team decisions. Existing agent-based approaches only guarantee unanimity in teams negotiating in domains exclusively composed of predictable and compatible issues. This article presents a model for negotiation teams that guarantees unanimous team decisions in domains consisting of predictable and compatible, and also unpredictable issues. Moreover, the article explores the influence of using opponent, and team member models in the proposing strategies that team members use. Experimental results show that the team benefits if team members employ Bayesian learning to model their teammates' preferences.
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as hotel reservation, restaurant reservation, and visit plans personalized for each tourist. The Social-Net Tourism Recommender System is a tourism recommender
system that is based on agent technology and uses social networks as its basis for recommendations. Nevertheless, these systems face some problems. On the one hand information needs to be mantained up-to-date, which can result in a costly task if not performed automatically. On the other hand, it may be interesting to include third parties services in the recommendation since they improve the quality of the recommendations. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing
techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third parties services that are not offered by service providers inside the system.
for negotiation teams that negotiate a deal with an opponent
is presented. Agent-based negotiation teams are groups of agents that join together as a single negotiation party because they share an interest that is related to the negotiation process. The model relies on a trusted mediator that coordinates and helps team members in the decisions that they have to take during the negotiation process: which offer is sent to the opponent, and whether or not the offers received from the opponent are accepted. The main strength of the proposed negotiation model is the fact that it guarantees unanimity within team decisions since decisions report a utility to team members that is greater than or equal to their aspiration levels at each negotiation round.
This work analyzes how unanimous decisions are taken within
the team and the robustness of the model against different types of manipulations. An empirical evaluation is also performed to study the impact of the different parameters of the model.
as hotel reservation, restaurant reservation, and visit plans personalized for each tourist. The Social-Net Tourism Recommender System is a tourism recommender
system that is based on agent technology and uses social networks as its basis for recommendations. Nevertheless, these systems face some problems. On the one hand information needs to be mantained up-to-date, which can result in a costly task if not performed automatically. On the other hand, it may be interesting to include third parties services in the recommendation since they improve the quality of the recommendations. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing
techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third parties services that are not offered by service providers inside the system.
for negotiation teams that negotiate a deal with an opponent
is presented. Agent-based negotiation teams are groups of agents that join together as a single negotiation party because they share an interest that is related to the negotiation process. The model relies on a trusted mediator that coordinates and helps team members in the decisions that they have to take during the negotiation process: which offer is sent to the opponent, and whether or not the offers received from the opponent are accepted. The main strength of the proposed negotiation model is the fact that it guarantees unanimity within team decisions since decisions report a utility to team members that is greater than or equal to their aspiration levels at each negotiation round.
This work analyzes how unanimous decisions are taken within
the team and the robustness of the model against different types of manipulations. An empirical evaluation is also performed to study the impact of the different parameters of the model.