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A belief revision approach for argumentation-based negotiation agents

Pablo Pilotti, Ana Casali, Carlos Chesñevar (2015)

International Journal of Applied Mathematics and Computer Science

Negotiation is an interaction that happens in multi-agent systems when agents have conflicting objectives and must look for an acceptable agreement. A typical negotiating situation involves two agents that cannot reach their goals by themselves because they do not have some resources they need or they do not know how to use them to reach their goals. Therefore, they must start a negotiation dialogue, taking also into account that they might have incomplete or wrong beliefs about the other agent's...

A generalization of the graph Laplacian with application to a distributed consensus algorithm

Guisheng Zhai (2015)

International Journal of Applied Mathematics and Computer Science

In order to describe the interconnection among agents with multi-dimensional states, we generalize the notion of a graph Laplacian by extending the adjacency weights (or weighted interconnection coefficients) from scalars to matrices. More precisely, we use positive definite matrices to denote full multi-dimensional interconnections, while using nonnegative definite matrices to denote partial multi-dimensional interconnections. We prove that the generalized graph Laplacian inherits the spectral...

A matrix inequality based design method for consensus problems in multi-agent systems

Shohei Okuno, Joe Imae, Tomoaki Kobayashi (2009)

International Journal of Applied Mathematics and Computer Science

In this paper, we study a consensus problem in multi-agent systems, where the entire system is decentralized in the sense that each agent can only obtain information (states or outputs) from its neighbor agents. The existing design methods found in the literature are mostly based on a graph Laplacian of the graph which describes the interconnection structure among the agents, and such methods cannot deal with complicated control specification. For this purpose, we propose to reduce the consensus...

A multi-agent brokerage platform for media content recommendation

Bruno Veloso, Benedita Malheiro, Juan Carlos Burguillo (2015)

International Journal of Applied Mathematics and Computer Science

Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer...

A strategy learning model for autonomous agents based on classification

Bartłomiej Śnieżyński (2015)

International Journal of Applied Mathematics and Computer Science

In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation...

Application of agent-based simulated annealing and tabu search procedures to solving the data reduction problem

Ireneusz Czarnowski, Piotr Jędrzejowicz (2011)

International Journal of Applied Mathematics and Computer Science

The problem considered concerns data reduction for machine learning. Data reduction aims at deciding which features and instances from the training set should be retained for further use during the learning process. Data reduction results in increased capabilities and generalization properties of the learning model and a shorter time of the learning process. It can also help in scaling up to large data sources. The paper proposes an agent-based data reduction approach with the learning process executed...

Bio-inspired decentralized autonomous robot mobile navigation control for multi agent systems

Alejandro Rodriguez-Angeles, Luis-Fernando Vazquez Chavez (2018)

Kybernetika

This article proposes a decentralized navigation controller for a group of differential mobile robots that yields autonomous navigation, which allows reaching a certain desired position with a specific desired orientation, while avoiding collisions with dynamic and static obstacles. The navigation controller is constituted by two control loops, the so-called external control loop is based on crowd dynamics, it brings autonomous navigation properties to the system, the internal control loop transforms...

Consensus and trajectory tracking of SISO linear multi-agent systems under switching communication topologies and formation changes

Carlos López-Limón, Javier Ruiz, Alejandro Cervantes-Herrera, Antonio Ramírez-Treviño (2013)

Kybernetika

The simultaneous problem of consensus and trajectory tracking of linear multi-agent systems is considered in this paper, where the dynamics of each agent is represented by a single-input single-output linear system. In order to solve this problem, a distributed control strategy is proposed in this work, where the trajectory and the formation of the agents are achieved asymptotically even in the presence of switching communication topologies and smooth formation changes, and ensuring the closed-loop...

Consensus seeking in multi-agent systems with an active leader and communication delays

Lixin Gao, Yutao Tang, Wenhai Chen, Hui Zhang (2011)

Kybernetika

In this paper, we consider a multi-agent consensus problem with an active leader and variable interconnection topology. The dynamics of the active leader is given in a general form of linear system. The switching interconnection topology with communication delay among the agents is taken into consideration. A neighbor-based estimator is designed for each agent to obtain the unmeasurable state variables of the dynamic leader, and then a distributed feedback control law is developed to achieve consensus....

Design of a Participatory Decision Making Agent Architecture Based on Argumentation and Influence Function – Application to a Serious Game about Biodiversity Conservation

Alessandro Sordoni, Jean-Pierre Briot, Isabelle Alvarez, Eurico Vasconcelos, Marta de Azevedo Irving, Gustavo Melo (2010)

RAIRO - Operations Research

This paper addresses an ongoing experience in the design of an artificial agent taking decisions and combining them with the decisions taken by human agents. The context is a serious game research project, aimed at computer-based support for participatory management of protected areas (and more specifically national parks) in order to promote biodiversity conservation and social inclusion. Its objective is to help various stakeholders (e.g., environmentalist, tourism operator) to collectively understand...

FSP and FLTL framework for specification and verification of middle-agents

Amelia Bădică, Costin Bădică (2011)

International Journal of Applied Mathematics and Computer Science

Agents are a useful abstraction frequently employed as a basic building block in modeling service, information and resource sharing in global environments. The connecting of requester with provider agents requires the use of specialized agents known as middle-agents. In this paper, we propose a formal framework intended to precisely characterize types of middle-agents with a special focus on matchmakers, brokers and front-agents by formally modeling their interactions with requesters and providers....

Predictive control for trajectory tracking and decentralized navigation of multi-agent formations

Ionela Prodan, Sorin Olaru, Cristina Stoica, Silviu-Iulian Niculescu (2013)

International Journal of Applied Mathematics and Computer Science

This paper addresses a predictive control strategy for a particular class of multi-agent formations with a time-varying topology. The goal is to guarantee tracking capabilities with respect to a reference trajectory which is pre-specified for an agent designed as the leader. Then, the remaining agents, designed as followers, track the position and orientation of the leader. In real-time, a predictive control strategy enhanced with the potential field methodology is used in order to derive a feedback...

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