A Framework for Argumentation-Based Agent Negotiation in Uncertain Settings

Automated negotiation technologies are being increasingly used in business applications, especially in the e-Commerce domain. Argumentation-Based Negotiation (ABN), among the existing approaches, has been distinguished as a powerful approach to automated negotiation due to its ability to provide more sophisticated information (arguments) that justifies and supports agents’ proposals in order to mutually influence their preference relations on the set of offers, and consequently on the negotiation outcome. During the recent years, argumentation-based negotiation has received a considerable attention in the area of agent communication. However, current proposals are mostly concerned with presenting protocols for showing how agents can interact with each other, and how arguments and offers can be generated, evaluated and exchanged under the assumption of certainty. Therefore, none of these proposals is directly targeting the agents’ uncertainty about the selection of their moves nor designing the appropriate negotiation strategies based on this uncertainty in order to help the negotiating agents better make their decisions in the negotiation settings where agents have limited or uncertain information, precluding them from making optimal individual decisions. In this thesis, we tackle the aforementioned problems by advocating an Argumentation-Based Agent Negotiation (ABAN) framework that is capable of handling the problem of agents’ uncertainty during the negotiation process. We begin by proposing an argumentation framework enriched with a new element called agent’s uncertainty as an important parameter in the agent theory to allow negotiating agents to decide which moves to play and reason about the selection of these moves under the assumption of uncertainty. Then, a method for agents’ uncertainty assessment is presented. In particular, we use Shannon entropy to assess agent’s uncertainty about their moves at each dialogue step as well as for the whole dialogue. Negotiation strategies and agent profiles issues are also explored and a methodology for designing novel negotiation strategies and agent profiles under the assumption of uncertainty is developed. Moreover, two important outcome properties namely, completeness and Nash equilibrium are discussed. Finally, the applicability of our framework is explored through several scenarios of the well-known Buyer/Seller case study. The obtained empirical results confirm the effectiveness of using our uncertainty-aware techniques and demonstrate the usefulness of using such techniques in argumentation-based negotiations

Procedurally Rhetorical Verb-Centric Frame Semantics as a Knowledge Representation for Argumentation Analysis of Biochemistry Articles

The central focus of this thesis is rhetorical moves in biochemistry articles. Kanoksilapatham has provided a descriptive theory of rhetorical moves that extends Swales' CARS model to the complete biochemistry article. The thesis begins the construction of a computational model of this descriptive theory. Attention is placed on the Methods section of the articles. We hypothesize that because authors' argumentation closely follows their experimental procedure, procedural verbs may be the guide to understanding the rhetorical moves. Our work proposes an extension to the normal (i.e., VerbNet) semantic roles especially tuned to this domain. A major contribution is a corpus of Method sections that have been marked up for rhetorical moves and semantic roles. The writing style of this genre tends to occasionally omit semantic roles, so another important contribution is a prototype ontology that provides experimental procedure knowledge for the biochemistry domain. Our computational model employs machine learning to build its models for the semantic roles and rhetorical moves, validated against a gold standard reflecting the annotation of these texts by human experts. We provide significant insights into how to derive these annotations, and as such have contributions as well to the general challenge of producing markups in the domain of biomedical science documents, where specialized knowledge is required

Dynamics in Formal Argumentation

Centre for Intelligent Systems and their ApplicationsIn this thesis we are concerned with the role of formal argumentation in artificial intelligence, in particular in the field of knowledge engineering. The intuition behind argumentation is that one can reason with imperfect information by constructing and weighing up arguements intended to give support in favour or against alternative conclusions. In dynamic argumentation, such arguements may be revised and strengthened in order yo increase to decrease the acceptability of controversial positions. This thesis studies the theory, architecture, development and applications of formal arguementation systems from the procedural perspective of actually generating argumentation processes. First, the types of problems that can be tackled via the argumentation paradigm in knowledge engineering are characterised. Second, an abstract formal framework are built from an underlying set of axioms, represented here as executatble logic programs. Finally an architecture for dynamic arguementation systems is defined, and domain-specific applications are presented within different domaind, thus grounding problems with very distinctive characteristics into a similar source in argumentation. The methods and definitions desribed in this thesis have been assessed on various bases, including the reconstruction of informal arguements and of arguments captured by existing formalisms, the relation between our framework and these formalisms, and examples of dynamic argumentation applications in the safety-engineering and multi-agent domains

Bridging the specification protocol gap in argumentation

As multi-agent systems (MAS) have become more mature and systems in general have become more distributed, it is necessary for those who want to build large scale systems to consider, in some computational depth, how agents can communicate in large scale, complex and distributed systems. Currently, some MAS systems have been developed to use an abstract specification language for argumentation. This as a basis for agent communication; to provide effective decision support for agents and yield better agreements. However, as we build complete MAS that involve argumentation, there is a need to produce concrete implementations in which these abstract specifications are realised via protocols coordinating agent behaviour. This creates a gap between standard argument specification and deployment of protocols. This thesis attempts to close this gap by using a combination of automated synthesis and verification methods. More precisely, this thesis proposes a means of moving rapidly from argument specification to protocol implementation using an extension of the Argument Interchange Format (AIF is a generic specification language for argument structure) called a Dialogue Interaction Diagram (DID) as the dialogue game specification language and the Lightweight Coordination Calculus (LCC is an executable specification language used for coordinating agents in open systems) as an implementation language. The main contribution of this research is to provide approaches for enabling developers of dialogue game argumentation systems to use specification languages (in our case AIF/DID) to generate agent protocol systems that are capable of direct implementation on open infrastructures (in our case LCC)

A study of multiple perspectives and knowledge in adverse drug reaction decision-making : Volume 1

Injury and illness associated with drugs are major problems in Australia and around the world, despite significant developments in the area of adverse drug reaction (ADR) decision support technology. The aims of this thesis are: to investigate the ADR decision domain; to determine factors that may assist in the prevention, detection and management of ADRs; and, to inform the pre-requirements analysis phase of the development of decision support systems. An approach has been taken that permits open and grounded study of the decision environment. This approach can then be used to frame and inform the design of an ADR decision support system. Fifteen case studies that comprise self selected consumers, the treating medical practitioner/s and expert perspectives of a single instance of an ADR (fifteen in-depth consumer interviews, eight in-depth medical practitioner interviews and 30 expert written questionnaires), have been collected and analysed using a grounded theory approach, a symbolic interactionist theoretical framework and a social constructionist epistemology. The analysis was performed from three perspectives: individual case study analysis (all interviews for an instance of an ADR); group analysis (consumer, medical practitioner and expert views) and analysis combining the individual case studies and groups of data. Concepts, themes and theory have emerged from these data in the following areas: • the contribution of the differences in understanding of the core concepts within this domain, to misunderstandings between decision-makers; • the consumer as a diagnostic decision-maker in the ADR decision domain; • differential diagnostic strategies used by the consumers and medical practitioners; • complexities in the ADR decision domain that make diagnosis difficult; • the role of ADR information in consumer and medical practitioner decision-making; • decision types used by consumers and medical practitioners in the ADR decision domain; • resources used by consumers, medical practitioners and experts to inform their ADR decisions; • decision-making with partial knowledge of the consumer case history, drug behaviour and diseases; • the impact of suspected ADRs on consumers and on future decision-making; • medical practitioner/consumer decision-making models; and, • reasons for low ADR reporting and the impact on the development of new ADR knowledge. The results above suggest the following: • The ADR decision domain is more complex than the current ADR decision support focus and that broadening this focus may assist in providing a more complete and useful decision support solution. • Improving the prevention, detection and management of ADRs requires more than providing prescribers with up to date ADR information. Other important factors are sharing of information, awareness of the role of the consumer, a collaborative approach between the consumers and medical practitioners, and generation of new ADR knowledge. • A grounded theory analysis of case study data using the theoretical perspectives of social constructionism and symbolic interactionism provided insight into this domain from the perspectives of multiple decision-makers. This may be an approach that can be used by systems analysts to inform the requirements analysis phases of decision support within other domains. The results of this qualitative work are preliminary. Future work is required to confirm and expand these results.Doctor of Philosoph

Modelling a conversational agent (Botocrates) for promoting critical thinking and argumentation skills

Students in higher education institutions are often advised to think critically, yet without being guided to do so. The study investigated the use of a conversational agent (Botocrates) for supporting critical thinking and academic argumentation skills. The overarching research questions were: can a conversational agent support critical thinking and academic argumentation skills? If so, how? The study was carried out in two stages: modelling and evaluating Botocrates' prototype. The prototype was a Wizard-of-Oz system where a human plays Botocrates' role by following a set of instructions and knowledge-base to guide generation of responses. Both stages were conducted at the School of Education at the University of Leeds. In the first stage, the study analysed 13 logs of online seminars in order to define the tasks and dialogue strategies needed to be performed by Botocrates. The study identified two main tasks of Botocrates: providing answers to students' enquiries and engaging students in the argumentation process. Botocrates’ dialogue strategies and contents were built to achieve these two tasks. The novel theoretical framework of the ‘challenge to explain’ process and the notion of the ‘constructive expansion of exchange structure’ were produced during this stage and incorporated into Botocrates’ prototype. The aim of the ‘challenge to explain’ process is to engage users in repeated and constant cycles of reflective thinking processes. The ‘constructive expansion of exchange structure’ is the practical application of the ‘challenge to explain’ process. In the second stage, the study used the Wizard-of-Oz (WOZ) experiments and interviews to evaluate Botocrates’ prototype. 7 students participated in the evaluation stage and each participant was immediately interviewed after chatting with Botocrates. The analysis of the data gathered from the WOZ and interviews showed encouraging results in terms of students’ engagement in the process of argumentation. As a result of the role of ‘critic’ played by Botocrates during the interactions, users actively and positively adopted the roles of explainer, clarifier, and evaluator. However, the results also showed negative experiences that occurred to users during the interaction. Improving Botocrates’ performance and training users could decrease users’ unsuccessful and negative experiences. The study identified the critical success and failure factors related to achieving the tasks of Botocrates