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...

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.