Argumentation in Multi-Agent Systems (original) (raw)
Argumentation in multi-agent systems: Context and recent developments
2007
The theory of argumentation [81] isa rich, interdisciplinary area of research lying across philosophy, communication studies, linguistics, and psychology. Its techniques and results have found a wide range of applications in both theoretical and practical branches of artificial intelligence and computer science [14,74]. These applications range from specifying semantics for logic programs [20], to natural language text generation [21], to supporting legal reasoning [9], to decision-support for multi-party human decision-making [31] and conflict resolution [80].
A computational model of argumentation schemes for multi-agent systems
Argument & Computation
There are many benefits of using argumentation-based techniques in multi-agent systems, as clearly shown in the literature. Such benefits come not only from the expressiveness that argumentation-based techniques bring to agent communication but also from the reasoning and decision-making capabilities under conditions of conflicting and uncertain information that argumentation enables for autonomous agents. When developing multi-agent applications in which argumentation will be used to improve agent communication and reasoning, argumentation schemes (reasoning patterns for argumentation) are useful in addressing the requirements of the application domain in regards to argumentation (e.g., defining the scope in which argumentation will be used by agents in that particular application). In this work, we propose an argumentation framework that takes into account the particular structure of argumentation schemes at its core. This paper formally defines such a framework and experimentally...
A systematic review of argumentation techniques for multi-agent systems research
Artificial Intelligence Review, 2015
The ability to build arguments that express thoughts is crucial for intelligent interactions among human beings. Thus, argumentation techniques have been applied for years in fields, such as rhetoric or artificial intelligence. More specifically, the agents paradigm fits into the use of these types of techniques because agents shape a society in which they interact to make arrangements or to decide future actions. Those interactions can be modelled using argumentation techniques. Therefore, the application of those techniques in multi-agent systems is an interesting research field. However, no systematic review has been conducted previously, to the best of the authors' knowledge, to provide an overview of argumentation techniques for multi-agent systems. This paper presents a systematic review of argumentation techniques for multi-agent systems research. The period of time that is included in this review is from 1998 to 2014. The objective of this review is to obtain an overview of the existing approaches and to study their impact on research and practice. The research method has been defined to identify relevant studies based on a predefined search strategy, and it is clearly defined to facilitate the reading of this paper. All of the included studies in this review have been analysed from two different points of view: the Application view and the Multi-Agent System view. A comprehensive analysis of the extracted data is provided in the paper, which is based on a set of research questions that are defined. The results of this review reveal suggestions for further research and practice. The argumentation technology is actually in a phase of internal enhancement and exploration. Moreover, the research interest in this topic has increased in the last years. Furthermore, several interesting findings are presented in the paper.
Towards Practical Argumentation in Multi-agent Systems
2015 Brazilian Conference on Intelligent Systems (BRACIS), 2015
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.
Argumentation and multi-agent decision making
1998
One focus of our work at Queen Mary and Westfield College is the development of multi-agent systems which deal with real world problems, an example being the diagnosis of faults in electricity distribution networks (Jennings et al. 1996). These systems are mixed-initiative in the sense that they depend upon interactions between agents--no single agent has sufficient skills or resources to carry out the tasks which the multi-agent system as a whole is faced with.
Towards Practical Argumentation-Based Dialogues in Multi-agent Systems
2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015
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 formallygrounded 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.
ABA: Argumentation Based Agents
Lecture Notes in Computer Science, 2012
Many works have identified the potential benefits of using argumentation in multiagent settings, as a way to implement the capabilities of agents (eg. decision making, communication, negotiation) when confronted with specific multiagent problems. In this paper we take this idea one step further and develop the concept of a fully integrated argumentation-based agent architecture. Under this architecture, an agent is composed of a collection of modules each of which is responsible for a basic capability or reasoning task of the agent. A local argumentation theory in the module gives preferred decision choices for the module's task in a way that is sensitive to the way the agent is currently situated in its external environment. The inter-module coordination or intra-agent control also relies on a local argumentation theory in each module that defines an internal communication policy between the modules. The paper lays the foundations of this approach, presents an abstract agent architecture and gives the general underlying argumentation machinery minimally required for building such agents, including the important aspects of inter-module coordination via argumentation. It presents the basic properties that we can expect from these agents and illustrates the possibility of this type of agent design with its advantages of high-level of flexibility and expressiveness.
An Argumentation-Based Framework for Deliberation in Multi-agent Systems
2007
This paper focuses of the group judgments obtained from a committee of agents that use deliberation. The deliberative process is realized by an argumentation framework called AMAL. The AMAL framework is completely based on learning from examples: the argument preference relation, the argument generation policy, and the counterargument generation policy are case-based techniques. For join deliberation, learning agents share their experience by forming a committee to decide upon some joint decision. We experimentally show that the deliberation in committees of agents improves the accuracy of group judgments. We also show that a voting scheme based on assessing the confidence of arguments improves the accuracy of group judgments than majority voting.
Negotiation and Argumentation in Multi-Agent Systems
2014
Argumentation-based negotiation (ABN) is a prevailing approach for automated negotiation. It is based on the exchange of arguments that allow an agent to acquire additional information about the other agents and the particular circumstances of the negotiation, and can be used for attacking or justifying offers. This is an important element in resolving conflicts that very often are due to the assumptions agents have made when making decisions and which may be found to be false in the course of the negotiation. Argumentation-based negotiation can be characterized in terms of three main topics, namely a) the reasoning mechanisms the agents use for negotiating and which are based on argumentation, b) the protocols the agents use for conveying arguments and offers and, c) the strategies that determine their choices at each step of the negotiation. This chapter presents argumentationbased negotiation by discussing representative works dealing with these three topics.
Formal properties of the SCIFF-AF Multi-Agent Argumentation Framework
Abstract. Argumentation theories have recently emerged and gained popularity in the agents community, since argumentation represents a natural and intuitive way to model non-monotonic reasoning. In a multiagent context, argumentation has recently been proposed as a component of dialogue frameworks. However, despite the large interest in argumentation theories in multiagent domains, most proposed frameworks stay at a general though abstract level, and operational counterparts to abstract frameworks are not many.
Meta-Information and Argumentation in Multi-Agent Systems
iSys - Brazilian Journal of Information Systems, 2017
In this work we compile our research regarding meta-information in multi-agent systems. In particular, we describe some agents profiles represent- ing different attitudes which describe how agents consider meta-information in their decisions-making and reasoning processes. Furthermore, we describe how we have combined different meta-information available in multi-agent systems with an argumentation-based reasoning mechanism. In our approach, agents are able to decide more conflicts between information/arguments, given that they are able to use different meta-information (often combined) to decide between such conflicting information. Our framework for meta-information in multi- agent systems was implemented based on a modular architecture, thus other meta-information can be added, as well as different meta-information can be combined in order to create new agents profiles. Therefore, in our approach, different agents profiles can be instantiated for different application domains, al...
Towards a Formal and Implemented Model of Argumentation Schemes in Agent Communication
Autonomous Agents and Multi-Agent Systems, 2005
Argumentation schemes are patterns of non-deductive reasoning that have long been studied in argumentation theory, and have more recently been identified in computational domains including multi-agent systems as holding the potential for significant improvements in reasoning and communication abilities. By focusing on models of natural language argumentation schemes, and then building formal systems from them, direct implementation becomes possible that not only has advantages in flexibility and scope, but also computational efficiency. ). But schemes, as construed by argumentation theory, seem to provide a somewhat more fine-grained analysis that is typical within AI. One example lies in the granularity of classification of types: Kienpointner introduces over a dozen, Walton, almost thirty, Grennan, over fifty, , over one hundred --and none claim exhaustivity. By comparison, AI systems are more typically built with a small handful (Pollock's (1995) OSCAR, for example identifies less than ten --with an uneven amount of work spread between them). This profligacy in philosophical classification might be argued to be as much a problem as an advantage -this is explored further below -but it serves to demonstrate that more detail is in some way being adduced. In particular, the propositional logic upon which a great deal of multi-agent argumentation is based is being further analysed to yield more refined structures of reasoning. It is the contention of this paper that those refined structures of reasoning yield well to a computational interpretation, and can be implemented to useful effect.
Multi-agent agreements about actions through argumentation
2006
Abstract. In this work, we propose a declarative multi-agent argumentation framework for reasoning and argument about actions, equipped with a sound operational model. The foundations of this framework rely on previous results from ALP and from Dung's studies on argumentation. Our approach features declarative knowledge representation and logic based reasoning, agent interaction by argumentation dialogues, and a notion of agreement about actions. Keywords.
Multiagent and Grid Systems, 2011
Case-Based Reasoning (CBR) can give agents the capability of learning from their own experience and solve new problems, however, in a multi-agent system, the ability of agents to collaborate is also crucial. In this paper we present an argumentation framework (AMAL) designed to provide learning agents with collaborative problem solving (joint deliberation) and information sharing capabilities (learning from communication). We will introduce the idea of CBR multi-agent systems (MAC systems), outline our argumentation framework and provide several examples of new tasks that agents in a MAC system can undertake thanks to the argumentation processes.
A Framework for Multiagent Deliberation Based on Dialectical Argumentation
Simply put, a multiagent system can be seen as a collection of autonomous agents that as a whole are able to accomplish goals beyond the reach of any of its members. Agent interaction is widely acknowledged as the feature that provides this added potential. Since many, if not all, of the attractive agent interactions can be recasted as deliberations, a formalization for this process is being actively seek.
A Customer Support Application Using Argumentation in Multi-Agent Systems
Multi-Agent Systems are suitable to provide a framework that allows to perform collaborative processes in distributed environments. In a customer support system with operators attending incidences, the problem to solve is to find out the best solution for the problems reported to the system. Each operator can have its own view about which is the best solution in each case and thus, conflicts of opinion among agents arise. Therefore, to engage in an argumentation dialogue is a suitable way for a group of agents (representing operators) to obtain an agreement about the best solution to solve an incidence. In this paper, an argumentation framework for a Multi-Agent System applied to customer support is proposed to help agents to reach an agreement and jointly solve incidences.
Learning, Information Exchange, and Joint-Deliberation through Argumentation in Multi-agent Systems
2008
Case-Based Reasoning (CBR) can give agents the capability of learning from their own experience and solve new problems, however, in a multi-agent system, the ability of agents to collaborate is also crucial. In this paper we present an argumentation framework (AMAL) designed to provide learning agents with collaborative problem solving (joint deliberation) and information sharing capabilities (learning from communication). We will introduce the idea of CBR multi-agent systems ( mathcalMnormalfonttextsfAC\mathcal{M}{\normalfont \textsf{AC}}mathcalMnormalfonttextsfAC systems), outline our argumentation framework and provide several examples of new tasks that agents in a mathcalMnormalfonttextsfAC\mathcal{M}\normalfont \textsf{AC}mathcalMnormalfonttextsfAC system can undertake thanks to the argumentation processes.
The agent argumentation architecture revisited
2007
Abstract. The Agent Argumentation Architecture (AAA) has been recently proposed [1] as an abstract model by means of which an autonomous agent argues with itself to manage its motivations and arbitrate its possibly conflicting internal goals. In an attempt to show how the AAA model can be instantiated, we revisit the original model with a concrete argumentation framework illustrating how the internal dialectic process can be specified as a dialogue-game between internal components representing the agent's mental faculties.