Alison R. Panisson

Integrating Ontologies with Multi-Agent Systems through CArtAgO Artifacts

Several advantages can be obtained by allowing multi-agent systems to easily access ontologies, for example, in scenarios where agents make their decisions based on the knowledge provided by ontologies. Thus, this paper presents an infrastructure to allow the use of web ontologies in different agent-oriented platforms. The agents use this infrastructure layer as a tool for storing, accessing and querying domain-specific OWL ontologies. As a result, this layer allows an integration of agent platforms with semantic web data and ontologies. We exemplify in practice how agents, coded in one such platform, can use the proposed access layer to ontological reasoning engines, as well as which features can be obtained from it. The performance of this semantic infrastructure is evaluated and compared against usual knowledge representation in agent programming.

Towards Practical Argumentation-Based Dialogues in Multi-agent Systems

Although argumentation has been a prominent topic of research in artificial intelligence and in particular agent communication, there has been little work on practical (but provably sound) argumentation approaches integrated with agent programming languages. In this paper, we develop a formally-grounded mechanism for practical argumentation-based dialogues in an agent platform based on a multi-agent programming language. We formalise a protocol to govern such dialogues, where agents use an argumentation-based reasoning mechanism that has been implemented. We prove that dialogues following our protocol always terminate and that ideal solutions are reached under certain conditions. The protocol is simple but was shown to be useful in a multi-agent system application that supports teams of cooperating humans.

Semantic Representations of Agent Plans and Planning Problem Domains

Integrating knowledge representation approaches with agent programming and automated planning is still an open research challenge. To explore the combination of those techniques, we present a semantic model of planning domains that can be converted to both agent programming plans as well as planning problem definitions. Our approach allows the representation of agent plans using ontologies, enabling the integration of different formalisms since the knowledge in the ontology can be reused by several systems and applications. Ontologies enable the use of semantic reasoning in planning and agent systems, and such semantic web technologies are significant current research trends. This paper presents our planning ontology, exemplify its use with an instantiation, and shows how to translate between ontology, agent code, and planning specifications. Algorithms to convert between these formalisms are shown, and we also discuss future directions towards the integration of semantic representation, automated planning, and agent programming.

Knowledge Representation for Argumentation in Agent-Oriented Programming Languages

Argumentation in multi-agent systems provides both a mechanism for agent reasoning under uncertainty and conflicting information as well as for communication in a more elaborate way, allowing agents to understand each other through the exchange of additional information when compared to other forms of agent communication. Even though argumentation techniques can play an important role in multi-agent systems, little research has been carried out on the issues in integrating argumentation techniques and agent-oriented programming languages, which would allow the development of practical applications taking advantage of such combined techniques. In this work, we present an argumentation framework developed on the basis of an agent-oriented programming language. We cover mainly the practical aspects of such integration, focusing on the knowledge representation expressivity resulting from it. Our approach allows the development of multi-agent applications where agents are able to use arguments in their decision-making processes as well as for communication. The framework has been successfully used as part of the development of a healthcare multi-agent prototype application.

Applying ontologies and agent technologies to generate ambient intelligence applications

The specification of agent systems comprises different dimensions normally defined using distinct formalisms. Since this lack of a uniform representation makes harder to express how each level affects the others, we propose an ontology to integrate the formalisms that originally cover a single multi-agent system dimension. In doing this, we align semantic technologies and knowledge representation for agents, environments, and organisations providing agent-oriented designers with a unified approach for developing complex systems. In our approach, we represent the abstractions typical of each multi-agent system dimension as an ontology, and we exemplify both the use of such ontologies to model an eldercare application in the context of ambient intelligence and smart cities, as well as how the ontology concepts support coding in agent platforms. We discuss the implications of such integrated view for designing agents, and highlight its advantages for agent-based software development.

Towards Practical Argumentation in Multi-agent Systems

Argumentation is a key technique for reaching agreements in multi-agent systems. However, there are few practical approaches to develop multi-agent systems where agents engage in argumentation-based dialogues. In this paper, we give formal semantics to speech acts for argumentation-based dialogues in the context of an agent-oriented programming language. Our approach uses operational semantics and builds upon existing work that provides computationally grounded semantics for agent mental attitudes such as beliefs and goals. The paper also shows how our formal semantics can be used to prove properties of argumentation in multi-agent systems with direct reference to mental attitudes. We do so with an example of a proof sketch of termination of multi-agent dialogues under certain assumptions.

Using Preferences over Sources of Information in Argumentation-Based Reasoning

Argumentation-based reasoning plays an important role in agent reasoning and communication, yet little research has been carried out on the issues in integrating argumentation techniques into practical multi-agent platforms and the various sources of information in such systems. In this work, we extend an argumentation-based reasoning mechanism to take into account preferences over arguments supporting contrary conclusions, which in practice means the agent will be able to act more informedly, being able to decide on beliefs about which it would be otherwise ambivalent. Such preferences come from elements that are present or can be more easily obtained in the context of practical multi-agent programming platforms, such as multiple sources from which the information (used to construct the arguments) was acquired, as well as varying degrees of trust on them. Further, we introduce different agent profiles by varying the way certain operators are applied over the various information sources leading to the preferences over competing arguments in our approach. Unlike previous approaches, our approach accounts for multiple sources for a single piece of information and is based on an argumentation-based reasoning mechanism implemented on a multi-agent platform so arguably more computationally grounded than those approaches.

Argumentation Schemes in Multi-agent Systems: A Social Perspective.

Argumentation schemes are common patterns of arguments used in everyday discourse, as well as in contexts such as legal and scientific argumentation. The use of argumentation schemes may depend on the (social) context of the participating actors, the roles that they play in society, and so on. Based on this idea, this work proposes a conceptual and practical framework that combines argumentation schemes and social organisations in multi-agent systems. In our framework, the agents’ social context constrains the usage of argumentation schemes and their associated critical questions. The framework has been developed on top of an existing multi-agent systems development platform, and we argue that our approach has advantages over traditional uses of argumentation schemes such as requiring less communication in multi-agent systems.

Towards Multi-Level Semantics for Multi-Agent Systems

In multi-agent systems, changes in an agents mental state often reflect changes at the social level as well. Furthermore, most work on agent languages use structural operational semantics to formalise multi-agent systems. As multi-agent systems are complex systems, it is difficult to formalise all relevant aspects of such system as a single transition system, and even transition systems for a single agent can easily become cumbersome. In this paper, we propose a particular style of semantic rules that make it visually clearer how changes at one level of a multi-agent system require simultaneous changes in other levels of the system (where each component of each level is modelled as a separate transition system).

Challenges for evaluating mobile systems with moving users

The major challenge for usability tests on mobile systems is to reproduce the context in which they are used. This paper points out some of the main difficulties encountered in the evaluation of such mobile systems, considering the real context of the user. Considering the need to assess such applications on the users context, it was conducted a field study to evaluate an urban mobility system and, for this purpose, it was proposed a collection instrument, which can be used by the observer to take notes related to the evaluation, enabling various forms of content (observations, important points of the environment, users verbal utterances, etc.). Through the field study, it was evaluated the benefits of using the proposed instrument, as well as identifying some of the difficulties faced in this type of study, i.e., evaluation of mobile systems on the move.