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Katie Atkinson

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34 papers
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34

JAAMAS Journal 2026 Journal Article

A Dialogue Game Protocol for Multi-Agent Argument over Proposals for Action

  • Katie Atkinson
  • Trevor Bench-Capon
  • Peter McBurney

We present the syntax and semantics for a multi-agent dialogue game protocol which permits argument over proposals for action. The protocol, called the Persuasive Argument for Multiple Agents (PARMA) Protocol, embodies an earlier theory by the authors of persuasion over action which enables participants to rationally propose, attack, and defend, an action or course of actions (or inaction). We present an outline of both an axiomatic and a denotational semantics, and discuss implementation of the protocol, in the context of both human and artificial agents.

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FLAP Journal 2025 Journal Article

Computational Models of Legal Argument

  • Trevor Bench-Capon
  • Katie Atkinson
  • Floris Bex
  • Henry Prakken
  • Bart Verheij

This article reviews work on applications of argumentation-based dialogue. It takes both a broad view of dialogue and a broad view of what constitutes an application. It considers the full range of software tools that would be needed in constructing a software system that is capable of engaging in argumentation- based dialogue, along with complete applications, and includes both work that builds on formal models of dialogue, and that is more inspired by recent work on chatbots from natural language processing.

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AIJ Journal 2023 Journal Article

Explainable AI tools for legal reasoning about cases: A study on the European Court of Human Rights

  • Joe Collenette
  • Katie Atkinson
  • Trevor Bench-Capon

In this paper we report on a significant research project undertaken to design, implement and evaluate explainable decision-support tools for deciding legal cases. We provide a model of a legal domain, Article 6 of the European Convention on Human Rights, constructed using a methodology from the field of computational models of argument. We describe how the formal model has been developed, extended and transformed into practical tools, which were then used in evaluation exercises to determine the effectiveness and usability of the tools. The underpinning AI techniques used yield a level of explanation that is firmly grounded in legal reasoning and is also digestible by the target end users, as demonstrated through our evaluation activities. The results of our experimental evaluation show that on the first pass, our tool achieved an accuracy rate of 97% in matching the actual decisions of the cases and the user studies conducted gave highly encouraging results with respect to usability. As such, our project demonstrates how trustworthy AI tools can be built for a real world legal domain where critical needs of the end users are accounted for.

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AILAW Journal 2022 Journal Article

Thirty years of Artificial Intelligence and Law: the second decade

  • Giovanni Sartor
  • Michał Araszkiewicz
  • Katie Atkinson
  • Floris Bex
  • Tom van Engers
  • Enrico Francesconi
  • Henry Prakken
  • Giovanni Sileno

Abstract The first issue of Artificial Intelligence and Law journal was published in 1992. This paper provides commentaries on nine significant papers drawn from the Journal’s second decade. Four of the papers relate to reasoning with legal cases, introducing contextual considerations, predicting outcomes on the basis of natural language descriptions of the cases, comparing different ways of representing cases, and formalising precedential reasoning. One introduces a method of analysing arguments that was to become very widely used in AI and Law, namely argumentation schemes. Two relate to ontologies for the representation of legal concepts and two take advantage of the increasing availability of legal corpora in this decade, to automate document summarisation and for the mining of arguments.

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FLAP Journal 2021 Journal Article

Value-based Argumentation.

  • Katie Atkinson
  • Trevor J. M. Bench-Capon

Value-based argumentation is concerned with recognising, accounting for, and reasoning with, the social purposes promoted by agents’ beliefs and actions. Value-based argumentation frameworks extend Dung’s abstract argumentation frameworks by ascribing an additional property to arguments, representing the values they promote, and recognising audiences. Values are ordered according to the preferences of an audience (different audiences will have different preferences) and an attack is successful only if the value of the attacked argument is not preferred to its attacker by its audience. Arguments can be related to values through the use of an argumentation scheme, thus enabling us to structure value-based argumentation. We describe the motivation of valuebased argumentation, its formal description and properties, the argumentation scheme and its associated critical questions and some of the applications to which value-based argumentation has been put.

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AIJ Journal 2020 Journal Article

Explanation in AI and law: Past, present and future

  • Katie Atkinson
  • Trevor Bench-Capon
  • Danushka Bollegala

Explanation has been a central feature of AI systems for legal reasoning since their inception. Recently, the topic of explanation of decisions has taken on a new urgency, throughout AI in general, with the increasing deployment of AI tools and the need for lay users to be able to place trust in the decisions that the support tools are recommending. This paper provides a comprehensive review of the variety of techniques for explanation that have been developed in AI and Law. We summarise the early contributions and how these have since developed. We describe a number of notable current methods for automated explanation of legal reasoning and we also highlight gaps that must be addressed by future systems to ensure that accurate, trustworthy, unbiased decision support can be provided to legal professionals. We believe that insights from AI and Law, where explanation has long been a concern, may provide useful pointers for future development of explainable AI.

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AILAW Journal 2020 Journal Article

In memoriam Douglas N. Walton: the influence of Doug Walton on AI and law

  • Katie Atkinson
  • Trevor Bench-Capon
  • Floris Bex
  • Thomas F. Gordon
  • Henry Prakken
  • Giovanni Sartor
  • Bart Verheij

Abstract Doug Walton, who died in January 2020, was a prolific author whose work in informal logic and argumentation had a profound influence on Artificial Intelligence, including Artificial Intelligence and Law. He was also very interested in interdisciplinary work, and a frequent and generous collaborator. In this paper seven leading researchers in AI and Law, all past programme chairs of the International Conference on AI and Law who have worked with him, describe his influence on their work.

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AIJ Journal 2018 Journal Article

Taking account of the actions of others in value-based reasoning

  • Katie Atkinson
  • Trevor Bench-Capon

Practical reasoning, reasoning about what actions should be chosen, is highly dependent both on the individual values of the agent concerned and on what others choose to do. Hitherto, computational models of value-based argumentation for practical reasoning have required assumptions to be made about the beliefs and preferences of other agents. Here we present a new method for taking the actions of others into account that does not require these assumptions: the only beliefs and preferences considered are those of the agent engaged in the reasoning. Our new formalism draws on utility-based approaches and expresses the reasoning in the form of arguments and objections, to enable full integration with value-based practical reasoning. We illustrate our approach by showing how value-based reasoning is modelled in two scenarios used in experimental economics, the Ultimatum Game and the Prisoner's Dilemma, and we present an evaluation of our approach in terms of these experiments. The evaluation demonstrates that our model is able to reproduce computationally the results of ethnographic experiments, serving as an encouraging validation exercise.

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KER Journal 2017 Journal Article

Environmental effects on simulated emotional and moody agents

  • Joe Collenette
  • Katie Atkinson
  • Daan Bloembergen
  • Karl Tuyls

Abstract Psychological models have been used to simulate emotions within agents as part of the decision-making process. The body of this work has focussed on applying the process of decision making using emotions to social dilemmas, notably the Prisoner’s Dilemma. Previous work has focussed on agents which do not move around, with an initial analysis on how mobility and the environment can affect the decisions chosen. Additionally simulated mood has been introduced to the decision-making process. Exploring simulated emotions and mood to inform the decision-making process in multi-agent systems allows us to explore in further detail how outside influences can have an effect on different strategies. We expand and clarify aspects of how agents are affected by environmental differences. We show how emotional characters settle on an outcome without deviation by providing a formal proof. We validate how the addition of mood increases cooperation, while also showing how small groups achieve this quicker than large groups. Once pure defectors are added, to test the resilience of the cooperation achieved, we see that while agents with a low starting mood achieve a payoff closest to the pure defectors, they are reduced in numbers the most by the pure defectors.

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AILAW Journal 2016 Journal Article

A methodology for designing systems to reason with legal cases using Abstract Dialectical Frameworks

  • Latifa Al-Abdulkarim
  • Katie Atkinson
  • Trevor Bench-Capon

Abstract This paper presents a methodology to design and implement programs intended to decide cases, described as sets of factors, according to a theory of a particular domain based on a set of precedent cases relating to that domain. We use Abstract Dialectical Frameworks (ADFs), a recent development in AI knowledge representation, as the central feature of our design method. ADFs will play a role akin to that played by Entity–Relationship models in the design of database systems. First, we explain how the factor hierarchy of the well-known legal reasoning system CATO can be used to instantiate an ADF for the domain of US Trade Secrets. This is intended to demonstrate the suitability of ADFs for expressing the design of legal cased based systems. The method is then applied to two other legal domains often used in the literature of AI and Law. In each domain, the design is provided by the domain analyst expressing the cases in terms of factors organised into an ADF from which an executable program can be implemented in a straightforward way by taking advantage of the closeness of the acceptance conditions of the ADF to components of an executable program. We evaluate the ease of implementation, the performance and efficacy of the resulting program, ease of refinement of the program and the transparency of the reasoning. This evaluation suggests ways in which factor based systems, which are limited by taking as their starting point the representation of cases as sets of factors and so abstracting away the particular facts, can be extended to address open issues in AI and Law by incorporating the case facts to improve the decision, and by considering justification and reasoning using portion of precedents.

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AAMAS Conference 2016 Conference Paper

A Synergy Coalition Group Based Dynamic Programming Algorithm for Coalition Formation

  • Luke Riley
  • Katie Atkinson
  • Paul E. Dunne
  • TERRY R. PAYNE

Coalition formation in characteristic function games entails agents partitioning themselves into a coalition structure and assigning the numeric rewards of each coalition via a payoff vector. Various coalition structure generation algorithms have been proposed that guarantee that an optimal coalition structure is found. We present the Synergy Coalition Group-based Dynamic Programming (SCG- DP) algorithm that guarantees that an optimal coalition structure and a least core stable payoff vector is found. This is completed by extending the existing results for the Synergy Coalition Group (SCG) representation to show that only coalitions in the SCG are needed to find a weak-least core stable payoff vector. The SCG- DP algorithm builds on this result by performing only the search operations necessary to guarantee that coalitions in the SCG of the given characteristic function game are found. The number of operations required is significantly less for many coalition-value distributions compared to the original Dynamic Programming (DP) algorithm [34] that finds an optimal coalition structure (e. g. only ∼60% of DP’s coalition lookup operations are performed in SCG- DP for 18 agents using a normal coalition-value distribution). Our experimental results show that a lower bound for these operations in SCG-DP converges onto 50%. This is an increase on the ∼33% bound of the optimal dynamic programming (ODP) algorithm [14], but ODP does not search for a stable solution. General Terms Algorithms, Economics, Theory

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AILAW Journal 2016 Journal Article

Accommodating change

  • Latifa Al-Abdulkarim
  • Katie Atkinson
  • Trevor Bench-Capon

Abstract The third of Berman and Hafner’s early nineties papers on reasoning with legal cases concerned temporal context, in particular the evolution of case law doctrine over time in response to new cases and against a changing background of social values and purposes. In this paper we consider the ways in which changes in case law doctrine can be accommodated in a recently proposed methodology for encapsulating case law theories (the ANGELIC methodology based on Abstract Dialectical Frameworks), and relate these changes the sources of change identified by Berman and Hafner.

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ECAI Conference 2016 Conference Paper

Value Based Reasoning and the Actions of Others

  • Katie Atkinson
  • Trevor J. M. Bench-Capon

Practical reasoning, reasoning about what actions should be chosen, is highly dependent both on the individual values of the agent concerned and on what others choose to do. We discuss how value based argumentation about what to do can be performed without making assumptions about the preferences of the other agents. We then show how expected utility calculations relate to the value-based argumentation approach, and express the reasoning as arguments and objections, so that they can be integrated value-based practical reasoning. We illustrate our discussion with examples of value based reasoning in public goods games as used in experimental economics and present an initial evaluation of the approach in terms of these experiments.

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AAAI Conference 2015 Conference Paper

Distributing Coalition Value Calculations to Coalition Members

  • Luke Riley
  • Katie Atkinson
  • Paul Dunne
  • Terry Payne

Within characteristic function games, agents have the option of joining one of many different coalitions, based on the utility value of each candidate coalition. However, determining this utility value can be computationally complex since the number of coalitions increases exponentially with the number of agents available. Various approaches have been proposed that mediate this problem by distributing the computational load so that each agent calculates only a subset of coalition values. However, current approaches are either highly inefficient due to redundant calculations, or make the benevolence assumption (i. e. are not suitable for adversarial environments). We introduce DCG, a novel algorithm that distributes the calculations of coalition utility values across a community of agents, such that: (i) no inter-agent communication is required; (ii) the coalition value calculations are (approximately) equally partitioned into shares, one for each agent; (iii) the utility value is calculated only once for each coalition, thus redundant calculations are eliminated; (iv) there is an equal number of operations for agents with equal sized shares; and (v) an agent is only allocated those coalitions in which it is a potential member. The DCG algorithm is presented and illustrated by means of an example. We formally prove that our approach allocates all of the coalitions to the agents, and that each coalition is assigned once and only once.

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AIJ Journal 2014 Journal Article

Algorithms for decision problems in argument systems under preferred semantics

  • Samer Nofal
  • Katie Atkinson
  • Paul E. Dunne

For Dungʼs model of abstract argumentation under preferred semantics, argumentation frameworks may have several distinct preferred extensions: i. e. , in informal terms, sets of acceptable arguments. Thus the acceptance problem (for a specific argument) can consider deciding whether an argument is in at least one such extensions (credulously accepted) or in all such extensions (skeptically accepted). We start by presenting a new algorithm that enumerates all preferred extensions. Following this we build algorithms that decide the acceptance problem without requiring explicit enumeration of all extensions. We analyze the performance of our algorithms by comparing these to existing ones, and present experimental evidence that the new algorithms are more efficient with respect to the expected running time. Moreover, we extend our techniques to solve decision problems in a widely studied development of Dungʼs model: namely value-based argumentation frameworks (vafs). In this regard, we examine analogous notions to the problem of enumerating preferred extensions and present algorithms that decide subjective, respectively objective, acceptance.

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AAMAS Conference 2012 Conference Paper

Opinion Gathering Using a Multi-Agent Systems Approach to Policy Selection

  • Adam Wyner
  • Katie Atkinson
  • Trevor Bench-Capon

An important aspect of e-democracy is consultation, in which policy proposals are presented and feedback from citizens is received and assimilated so that these proposals can be refined and made more acceptable to the citizens affected by them. We present an innovative web-based application that uses recent developments in multi-agent systems (MAS) to provide intelligent support for opinion gathering, eliciting a structured critique within a highly usable system.

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JAAMAS Journal 2011 Journal Article

A framework for Multi-Agent Based Clustering

  • Santhana Chaimontree
  • Katie Atkinson
  • Frans Coenen

Abstract A framework to support Multi-Agent Based Clustering (MABC) is described. A unique feature of the framework is that it provides mechanisms to allow agents to negotiate so as to improve an initial cluster configuration. The framework encourages a two phase approach to clustering. During the first phase clustering agents bid for records in the input data and form an initial cluster configuration. In the second phase (the negotiation phase) agents pass individual records to each other so as to improve the initial configuration. The communication framework and its operation is fully described in terms of the performatives used and from an algorithmic perspective. The reported evaluation was conducted using benchmark data sets. The results demonstrate that the supported agent negotiation produces enhanced clustering results.

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AAMAS Conference 2011 Conference Paper

Choosing Persuasive Arguments for Action

  • Elizabeth Black
  • Katie Atkinson

We present a dialogue system that allows agents to exchange arguments in order to come to an agreement on how to act. When selecting arguments to assert, an agent uses a model of what is important to the recipient agent. The system lets the agents agree to an action that each finds acceptable, but does not necessarily demand that they resolve their differing preferences. We present an analysis of the behaviour of our system and develop a mechanism with which an agent can develop a model of another's preferences.

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JAAMAS Journal 2011 Journal Article

Using argumentation to model agent decision making in economic experiments

  • Trevor Bench-Capon
  • Katie Atkinson
  • Peter McBurney

Abstract In this paper we demonstrate how a qualitative framework for decision making can be used to model scenarios from experimental economic studies and we show how our approach explains the results that have been reported from such studies. Our framework is an argumentation-based one in which the social values promoted or demoted by alternative action options are explicitly represented. Our particular representation is used to model the Dictator Game and the Ultimatum Game, which are simple interactions in which it must be decided how a sum of money will be divided between the players in the games. Studies have been conducted into how humans act in such games and the results are not explained by a decision-model that assumes that the participants are purely self-interested utility-maximisers. Some studies further suggest that differences in choices made in different cultures may reflect their day to day behaviour, which can in turn be related to the values of the subjects, and how they order their values. In this paper we show how these interactions can be modelled in agent systems in a framework that makes explicit the reasons for the agents’ choices based upon their social values. Our framework is intended for use in situations where agents are required to be adaptable, for example, where agents may prefer different outcome states in transactions involving different types of counter-parties.

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AAMAS Conference 2009 Conference Paper

Dialogues that Account for Different Perspectives in Collaborative Argumentation

  • Elizabeth Black
  • Katie Atkinson

It is often the case that agents within a system have distinct types of knowledge. Furthermore, whilst common goals may be agreed upon, the particular representations of the individual agents’ views of the world that they operate within may not always match. In this paper we provide a framework to allow different agents with different expertise to make individual contributions to an overall reasoning process, in order to make a decision about how to act to achieve some goal. Our framework is based on a model of argumentation that embeds inquiry dialogues within a process of practical reasoning. We combine two different approaches to argumentative reasoning and show not only how they can function together within a formal framework to provide richer interactions, but also how this facilitates reasoning across distributed agents who may each have different perspectives on the scenarios they operate in.

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AILAW Journal 2009 Journal Article

Did he jump or was he pushed?

  • Floris Bex
  • Trevor Bench-Capon
  • Katie Atkinson

Abstract In this paper, we present a particular role for abductive reasoning in law by applying it in the context of an argumentation scheme for practical reasoning. We present a particular scheme, based on an established scheme for practical reasoning, that can be used to reason abductively about how an agent might have acted to reach a particular scenario, and the motivations for doing so. Plausibility here depends on a satisfactory explanation of why this particular agent followed these motivations in the particular situation. The scheme is given a formal grounding in terms of action-based alternating transition systems and we illustrate the approach with a running legal example.

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IS Journal 2009 Journal Article

Using Computational Argumentation to Support E-participation

  • Dan Cartwright
  • Katie Atkinson

Internet-based tools that encourage public participation in debates concerning policy issues have been recognized as a good way to engage the electorate with political issues. In addition, such systems for e-participation can gather, make available, and analyze the public's contributions to political debate. In this article we discuss a system called Parmenides, which we designed to exploit technological developments to bring democratic processes into the online world. Parmenides is primarily a forum by which government bodies can present policy proposals to the public so that users can submit their opinions on the justification presented for the particular policy. Within Parmenides, the justification for action is structured to exploit a specific representation of persuasive argument based on the use of argumentation schemes and critical questions.

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AAAI Conference 2007 Conference Paper

Action-Based Alternating Transition Systems for Arguments about Action

  • Katie Atkinson

This paper presents a formalism to describe practical reasoning in terms of an Action-based Alternating Transition System (AATS). The starting point is a previously specified account of practical reasoning that treats reasoning about what action should be chosen as presumptive argumentation using argument schemes and associated critical questions. This paper describes how this account can be extended to situations where the effect of an action is partially dependent upon the choices of another agent. In this context we see practical reasoning as proceeding in three stages. The first involves determining the representation of the particular problem scenario as an AATS. Next the agent must resolve its uncertainties as to its position in the scenario. Finally, the agent moves to choosing a particular action to achieve its ends, proposing presumptive reasons for particular actions and subjecting them to a critique to establish their suitability, taking into account the choices that can be made by the other agents involved. This account thus provides a well-specified basis for addressing the problems of practical reasoning as presumptive argumentation in a multi-agent context.

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AIJ Journal 2007 Journal Article

Practical reasoning as presumptive argumentation using action based alternating transition systems

  • Katie Atkinson
  • Trevor Bench-Capon

In this paper we describe an approach to practical reasoning, reasoning about what it is best for a particular agent to do in a given situation, based on presumptive justifications of action through the instantiation of an argument scheme, which is then subject to examination through a series of critical questions. We identify three particular aspects of practical reasoning which distinguish it from theoretical reasoning. We next provide an argument scheme and an associated set of critical questions which is able to capture these features. In order that both the argument scheme and the critical questions can be given precise interpretations we use the semantic structure of an Action-Based Alternating Transition System as the basis for their definition. We then work through a detailed example to show how this approach to practical reasoning can be applied to a problem solving situation, and briefly describe some other previous applications of the general approach. In a second example we relate our account to the social laws paradigm for co-ordinating multi-agent systems. The contribution of the paper is to provide firm foundations for an approach to practical reasoning based on presumptive argument in terms of a well-known model for representing the effects of actions of a group of agents.

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AILAW Journal 2006 Journal Article

PARMENIDES: Facilitating Deliberation in Democracies

  • Katie Atkinson
  • Trevor Bench-Capon
  • Peter McBurney

Abstract Governments and other groups interested in the views of citizens require the means to present justifications of proposed actions, and the means to solicit public opinion concerning these justifications. Although Internet technologies provide the means for such dialogues, system designers usually face a choice between allowing unstructured dialogues, through, for example, bulletin boards, or requiring citizens to acquire a knowledge of some argumentation schema or theory, as in, for example, ZENO. Both of these options present usability problems. In this paper, we describe an implemented system called PARMENIDES which allows structured argument over a proposed course of action, without requiring knowledge of the underlying argumentation theory.

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AILAW Journal 2005 Journal Article

Legal Case-based Reasoning as Practical Reasoning

  • Katie Atkinson
  • Trevor Bench-Capon

Abstract In this paper we apply a general account of practical reasoning to arguing about legal cases. In particular, we provide a reconstruction of the reasoning of the majority and dissenting opinions for a particular well-known case from property law. This is done through the use of Belief-Desire-Intention (BDI) agents to replicate the contrasting views involved in the actual decision. This reconstruction suggests that the reasoning involved can be separated into three distinct levels: factual and normative levels and a level connecting the two, with conclusions at one level forming premises at the next. We begin by summarising our general approach, which uses instantiations of an argumentation scheme to provide presumptive justifications for actions, and critical questions to identify arguments which attack these justifications. These arguments and attacks are organised into argumentation frameworks to identify the status of individual arguments. We then discuss the levels of reasoning that occur in this reconstruction and the properties and significance of each of these levels. We illustrate the different levels with short examples and also include a discussion of the role of precedents within these levels of reasoning.

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v2026.09.13