Mariela Morveli-Espinoza

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• Doctor of Science
• PostDoc Position at Umeå University

Task delegation in multi-agent systems (MASs) is crucial for ensuring efficient collaboration among agents with different capabilities and skills. Traditional delegation models rely on social mechanisms such as trust and reputation to evaluate potential partners. While these approaches are effective in selecting competent agents, they often lack tr...

This work presents an approach for distributed and contextualized reasoning in multi-agent systems, considering environments in which agents may have incomplete, uncertain and inconsistent knowledge. Knowledge is represented by defeasible logic with mapping rules, which model the capability of agents to acquire knowledge from other agents during re...

Human-aware Artificial Intelligent systems are goal-directed autonomous systems that are capable of interacting, collaborating, and teaming with humans. Some relevant tasks of these systems are recognizing human’s desires and intentions and exhibiting explicable behavior, giving cogent explanations on demand and engendering trust. This article tack...

As agent-based systems have been growing, more and more the general public has access to them and is influenced by decisions taken by these systems. This increases the necessity for such systems to be capable of explaining themselves to a user. The Beliefs-Desires-Intentions (BDI) is a commonly used agent model that has an two-phase internal goal s...

This work presents an approach for distributed and contextualized reasoning in multi-agent systems, considering environments in which agents may have incomplete, uncertain and inconsistent knowledge. Knowledge is represented by defeasible logic with mapping rules, which model the capability of agents to acquire knowledge from other agents during re...

The Bipolar Argumentation Framework approach is an extension of the Abstract Argumentation Framework. A Bipolar Argumentation Framework considers a support interaction between arguments, besides the attack interaction. As in the Abstract Argumentation Framework, some researches consider that arguments have a degree of uncertainty, which impacts on...

Explainable Artificial Intelligence systems, including intelligent agents, are expected to explain their internal decisions, behaviors and reasoning that produce their choices to the humans (or to other systems) with which they interact. Given this context, the aim of this article is to introduce a practical reasoning agent framework that supports...

In cooperative environments is common that agents delegate tasks to each other to achieve their goals since an agent may not have the capabilities or resources to achieve its objectives alone. However, to select good partners, the agent needs to deal with information about the abilities, experience, and goals of their partners. In this situation, t...

Human-aware Artificial Intelligent systems are goal directed autonomous systems that are capable of interacting, collaborating, and teaming with humans. Activity reasoning is a formal reasoning approach that aims to provide common sense reasoning capabilities to these interactive and intelligent systems. This reasoning can be done by considering ev...

Algoritmos de aprendizado de caminhos ótimos estão presentes em diversos cenários. Diante disso, o LRTA* (learning real time A*) surge como uma opção que concilia planejamento e ação. O presente artigo estuda como a variação da quantidade de agentes impacta nas distâncias percorridas por eles para encontrar o caminho ótimo utilizando o LRTA* em amb...

Em um sistema multi-agente (SMA), é muito comum que os agentes deleguem tarefas uns aos outros. Contudo, devido à subjetividade das informações utilizadas pelos agentes durante o processo de tomada de decisão, um agente pode acabar delegando uma tarefa a um parceiro não confiável. Neste trabalho, apresentamos uma abordagem de cálculo de confiança b...

Argumentation-based persuasive negotiation is a form of negotiation dialogue in which agents, with different interests and goals, exchange proposals that are supported by rhetorical arguments such as threats, rewards, or appeals. Besides rhetorical arguments, additional kinds of illocutions may also be exchanged during the dialogue, for instance, a...

This volume contains revised versions of the papers selected for the second volume of the Online Handbook of Argumentation for AI (OHAAI). Previously, formal theories of argument and argument interaction have been proposed and studied, and this has led to the more recent study of computational models of argument. Argumentation, as a field within ar...

In this study, we tackled the problem of distributed reasoning in environments in which agents may have incomplete and inconsistent knowledge. Conflicts between agents are resolved through defeasible argumentation-based semantics with a preference function. Support for dynamic environments, where agents constantly enter and leave the system, was ac...

Rhetorical arguments are used in negotiation dialogues when a proponent agent tries to persuade his opponent to accept a proposal more readily. When more than one argument is generated, the proponent must compare them in order to select the most adequate for his interests. A way of comparing them is by means of their strength values. Related work p...

The aim of this article is to propose a model for the measurement of the strength of rhetorical arguments (i.e., threats, rewards, and appeals), which are used in persuasive negotiation dialogues when a proponent agent tries to convince his opponent to accept a proposal. Related articles propose a calculation based on the components of the rhetoric...

During the first step of practical reasoning, i.e. deliberation or goals selection, an intelligent agent generates a set of pursuable goals and then selects which of them he commits to achieve. Explainable Artificial Intelligence (XAI) systems, including intelligent agents, must be able to explain their internal decisions. In the context of goals s...

In this paper, we extend previous work on distributed reasoning using Contextual Defeasible Logic (CDL), which enables decentralised distributed reasoning based on a distributed knowledge base, such that the knowledge from different knowledge bases may conflict with each other. However, there are many use case scenarios that are not possible to rep...

By considering rational agents, we focus on the problem of selecting goals out of a set of incompatible ones. We consider three forms of incompatibility introduced by Castelfranchi and Paglieri, namely the terminal, the instrumental (or based on resources), and the superfluity. We represent the agent's plans by means of structured arguments whose p...

argumentation approaches consider that arguments have a degree of uncertainty, which impacts on the degree of uncertainty of the extensions obtained from a abstract argumentation framework (AAF) under a semantics. In these approaches, both the uncertainty of the arguments and of the extensions are modeled by means of precise probability values. How...

During the first step of practical reasoning, i.e. deliberation or goals selection, an intelligent agent generates a set of pursuable goals and then selects which of them he commits to achieve. Explainable Artificial Intelligence (XAI) systems, including intelligent agents, must be able to explain their internal decisions. In the context of goals s...

Explainable Artificial Intelligence (XAI) systems, including intelligent agents, must be able to explain their internal decisions, behaviours and reasoning that produce their choices to the humans (or other systems) with which they interact. In this paper, we focus on how an extended model of BDI (Beliefs-Desires-Intentions) agents can be able to g...

An intelligent agent may in general pursue multiple procedural goals simultaneously, which may lead to arise some conflicts (incompatibilities) among them. In this paper, we focus on the incompatibilities that emerge due to resources limitations. Thus, the contribution of this article is twofold. On one hand, we give an algorithm for identifying re...

During the first step of practical reasoning, i.e. deliberation, an intelligent agent generates a set of pursuable goals and then selects which of them he commits to achieve. An intelligent agent may in general generate multiple pursuable goals, which may be incompatible among them. In this paper, we focus on the definition, identification and reso...

O problema de Agregação de Julgamento tem como objetivo unir o julgamento de vários indivíduos em um único conjunto para se chegar a um acordo do grupo. Utilizando a plataforma JaCaMo, uma ferramenta de três camadas, ambiente, sistema multiagente, e organizacional, este trabalho descreve a especificação do modelo de agregação de julgamento de Camin...

O objetivo deste artigo é propor uma arquitetura e discutir o design e implementação de um simulador de agentes baseados em Processamento de Objetivos Baseado em Crenças (BBGP). Uma implementação do modelo poderia ser empregada em estudos do modelo conceitual BBGP além de tornar mais simples a análise e explicação do processo de raciocínio do agent...

In multi-agent systems (MAS), computational reputation models have been adopted as an important solution in order to ensure security and efficiency. The evaluation mechanisms, offered by these models, can be used to punish inappropriate behaviors of agents and improve the partner selection process in uncertain situations. However, as the reputation...

Threats are used in persuasive negotiation dialogues when a proponent agent tries to persuade an opponent of him to accept a proposal. Depending on the information the proponent has modeled about his opponent(s), he may generate more than one threat, in which case he has to evaluate them in order to select the most adequate to be sent. One way to e...

Computational Argumentation has been applied successfully over legal disputes, especialy in consuetudinary law (case-based). In order to extend this approach to other legal systems-such as positive law-it is necessary to distinguish the backup of arguments based on past cases from the guarantees of the arguments based on positive laws. In this pape...

Argumentação computacional tem sido empregada com sucesso em problemas de disputas judiciais, principalmente no direito consuetudinário (baseado em precedentes). Para estender essa abordagem a outros sistemas -como o direito positivo- é necessário distinguir o respaldo dos argumentos baseados em precedentes das garantias dos argumentos baseados em...

Rhetorical arguments are used in negotiation dialogues when a proponent agent tries to persuade his opponent to accept a proposal more readily. When more than one argument is generated, the proponent must compare them in order to select the most adequate for his interests. A way of comparing them is by means of their strength values. Related articl...

By considering rational agents, we focus on the problem of selecting goals out of a set of incompatible ones. We consider three forms of incompatibility introduced by Castelfranchi and Paglieri, namely the terminal, the instrumental (or based on resources), and the superfluity. We represent the agent's plans by means of structured arguments whose p...

argumentation approaches consider that arguments have a degree of uncertainty, which impacts on the degree of uncertainty of the extensions obtained from a abstract argumentation framework (AAF) under a semantics. In these approaches, both the uncertainty of the arguments and of the extensions are modeled by means of precise probability values. How...

This paper presents a model of dialogue to support the common-knowledge formation in a group of agents which is based on the exchange of arguments supporting or rejecting an issue under discussion and other arguments during the dialogue. In the model, the agents play two roles: argumentative and mediator. Argumentative agents are responsible for bu...

In an argumentative dialogue, agents exchange arguments to approve or disapprove a decision alternative. The problem arises when a group of agents with incomplete information needs to reach consensus on the decision. This study proposes a framework for decision-making where the argumentative agents can build the necessary common knowledge to make a...

In this work, we present an argumentation-based formalization for supporting the process of formation of intentions in practical agents. This is based on the belief-based goal processing model proposed by Castelfranchi and Paglieri, which is a more expressive and refined model than the BDI (Beliefs-Desires-Intentions) model. We focus on the progres...

During the first step of practical reasoning, i.e. deliberation, an intelligent agent generates a set of pursuable goals and then selects which of them he commits to achieve. An intelligent agent may in general generate multiple pursuable goals, which may be incompatible among them. In this paper, we focus on the definition, identification and reso...

One of the challenges of rhetorical arguments is how to evaluate which argument is more suitable to send to an opponent in a specific situation. This work presents a fuzzy-based decision-making mechanism for agents to appropriately choose one argument among different rhetorical arguments. Some scenarios were developed and the results yielded by our...

An intelligent agent may in general pursue multiple procedural goals simultaneously, which may lead to arise some conflicts (incompatibilities) among them. In this paper, we focus on the incompatibilities that emerge due to resources limitations. Thus, the contribution of this article is twofold. On one hand, we give an algorithm for identifying re...

An intelligent agent may in general pursue multiple goals at the same time, which leads to arise some conflict among them. In this paper, we focus on these conflicts or incompatibilities among goals. Our approach is based on the model of Castelfranchi and Paglieri, in which, three forms of incompatibility and the criteria for selection of goals are...

A portfolio problem is about selecting one or several out of a set of possible items, considering some constraints, and where outcomes are determined by a form of aggregating the properties of the items selected. In this paper, we aim to study the use of abstract argumentation theory for a simplified version of the portfolio selection problem, wher...

Rewards are rhetorical arguments that have a positive nature since they use the argument that something positive will happen to the opponent if he accepts to do the proponent requirement. During a persuasive negotiation more than one reward can be generated and the proponent has to choose one to send to his opponent. Since one measure that could he...

Threats make part of the set of rhetorical arguments, which are used in negotiation dialogues when a proponent agent tries to persuade his opponent to accept a proposal more readily. When more than one threat is generated, the proponent must evaluate each and select the most adequate. One way of evaluation is calculating the strength of threats, si...

Persuasive negotiation involves negotiating using rhetorical arguments (such as threats, rewards, and appeals), which act as persuasive elements that aim to force or convince an opponent to accept a given proposal. In the case of rewards, these have a positive nature as they use the argument that something positive will happen to the opponent if he...

Diversos sistemas de argumentação aplicados na tomada de decisão em sistemas multiagentes foram propostos. No entanto, pouca atenção foi dada aos casos onde a decisão deve ser obtida de forma consensual. Apresentamos um protocolo para diálogos baseado em argumentação para apoio na tomada de decisão consensual onde o diálogo é dinâmico, não havendo...

Data-Oriented Belief Revision (DBR) is a relatively recent approach that claims the difference between pieces of information gathered and stored by agent (data) and information revised and considered reliable (beliefs). Data structure proposed in DBR can also be used to implement the structure of an argument. It’s worth noting that this approach ca...

In this paper we propose an architecture for deliberative agents based on progressive reasoning. When an agent receives a query, it tries to satisfy it by building an answer based on its current knowledge. Depending on the available time or the urgency of the requirement the agent can produce answers with different levels of quality. Agents could b...

When an agent receives a query from another agent, it tries to satisfy it by building an answer based on its current knowledge. Depending on the available time or the urgency of the requirement the agent can produce answers with different levels of quality. Answers can contain the best one, a provisional one because it can be improved later, or a c...

This paper presents the implementation of ARQ-PROP II, a limited-depth propositional neural reasoner based on the Resolution Principle. The SATyrus platform was used in the synthesis of Energy functions from a set of pseudo-Boolean constraints specifying ARQ-PROP II architectures for different inferencing depths. Global minima of the Energy functio...

Agents are situated autonomous entities that perceive and act in their environ- ment, and communicate with other agents. An agent usually starts a conversation by querying another agent because it needs to satisfy a specific goal. This process allocates a new goal to the agent receiving the initial query, starting new dialogs with other agents, gen...

This paper presents the implementation of ARQ-PROP II, a limited-depth propositional reasoner, via the compilation of its specification into an exact formulation using the satyrus platform. satyrus’ compiler takes as input the definition of a problem as a set of pseudo-Boolean constraints and produces, as output, the Energy function of a higher-ord...

This paper introduces a novel approach to the specification of hard combinatorial problems as pseudo-Boolean constraints. It is shown (i) how this set of constraints defines an energy landscape representing the space state of solutions of the target problem, and (ii) how easy is to combine different problems into new ones mostly via the union of th...

This paper introduces SATyrus, a neuro-symbolic architecture oriented to optimization problem solving via mapping problems specification into sets of pseudo-Boolean constraints. SATyrus provides a logical declarative language used to specify and compile a target problem into a particular energy function representing its space state of solutions. Th...

Predicting the three-dimensional geometry of a molecule is a key issue in, among other important research goals, the discovery of new drugs. This work introduces a novel way to synthesize the potential energy function of a target molecule from which arbitrary partial geometrical information is given. Assuming that the global minimization of the res...