Henry Prakken

• Utrecht University

We define and study the notions of stability and relevance for precedent-based reasoning, focusing on Horty’s result model of precedential constraint. According to this model, precedents constrain the possible outcomes for a focus case, which is a yet undecided case, where precedents and the focus case are compared on their characteristics (called...

In this paper we build on a formal model of reasoning with dimensions to analyze data from the COMPAS program—a widely used and studied tool for predicting recidivism. We extend the underlying theory of the model by introducing a notion of consistency and apply it to assess whether COMPAS follows this principle in its risk assessments and supervisi...

This paper investigates whether empirical findings on how humans evaluate arguments in reinstatement cases support the ‘fewer attackers is better’ principle, incorporated in many current gradual notions of argument acceptability. Through three variations of an experiment, we find that (1) earlier findings that reinstated arguments are rated lower t...

In recent years, a model of a fortiori argumentation, developed to describe legal reasoning based on precedent, has been successfully applied in the field of artificial intelligence to improve interpretability of data-driven decision systems. In order to make this model more broadly applicable for this purpose, work has been done to expand the know...

We extend the result model for precedent-based reasoning with incomplete case bases. In contrast to regular case bases, these consist of incomplete cases for which not all dimension values need to be specified, but rather each dimension is assigned a set of possible values. The outcome of cases then applies for each (combination of) the possible di...

We present Global Causal Analysis (GCA) for text classification. GCA is a technique for global model-agnostic explainability drawing from well-established observational causal structure learning algorithms. GCA generates an explanatory graph from high-level human-interpretable features, revealing how these features affect each other and the black-b...

This paper proposes a structured variant in ASPIC+ of the notion of expansions of abstract argumentation frameworks. The purpose of this is threefold: studying what it takes to instantiate the abstract notion of expansions with a structured account of argumentation, studying to which extent assumptions implicitly made at the abstract level hold for...

Widespread application of uninterpretable machine learning systems for sensitive purposes has spurred research into elucidating the decision making process of these systems. These efforts have their background in many different disciplines, one of which is the field of AI & law. In particular, recent works have observed that machine learning traini...

This paper formally studies a notion of dialectical argument strength in terms of the number of ways in which an argument can be successfully attacked in expansions of an abstract argumentation framework. The proposed model is abstract but its design is motivated by the wish to avoid overly limiting assumptions that may not hold in particular dialo...

In this paper we formalise a meta-argumentation framework as an ASPIC+ extension which enables reasoning about conflicts between formulae of the argumentation language. The result is a standard abstract argumentation framework that can be evaluated via grounded semantics.

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...

This paper proposes a formal top-level model of explaining the outputs of machine-learning-based decision-making applications and evaluates it experimentally with three data sets. The model draws on AI & law research on argumentation with cases, which models how lawyers draw analogies to past cases and discuss their relevant similarities and differ...

There has recently been talk of algorithms that predict decisions in legal cases being used by the judiciary to improve the predictability and consistency of judicial decision making. We argue that their use may minimise the error rate of decisions in the long run, but that this would require not only major technical advances but also major changes...

In this paper several recent factor- and dimension-based models of precedential constraint are formally investigated and an alternative dimension-based model is proposed. Simple factor- and dimension-based syntactic criteria are identified for checking whether a decision in a new case is forced, in terms of the relevant differences between a preced...

This paper proposes a classification of three aspects of argument strength based on philosophical insights, in particular Aristotle’s distinction between logic, dialectic and rhetoric. It is then argued that when developing or evaluating gradual accounts of argument strength it is essential to be explicit about which aspect of argument strength is...

In this paper, we present the information graph (IG) formalism, which provides a precise account of the interplay between deductive and abductive inference and causal and evidential information, where ‘deduction’ is used for defeasible ‘forward’ inference. IGs formalise analyses performed by domain experts in the informal reasoning tools they are f...

In this paper, we propose an argumentation formalism that allows for both deductive and abductive argumentation, where ‘deduction’ is used as an umbrella term for both defeasible and strict ‘forward’ inference. Our formalism is based on an extended version of our previously proposed information graph (IG) formalism, which provides a precise account...

Decisions concerning proof of facts in criminal law must be rational because of what is at stake, but the decision-making process must also be cognitively feasible because of cognitive limitations, and it must obey the relevant legal-procedural constraints. In this topic three approaches to rational reasoning about evidence in criminal law are comp...

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...

This anthology contains revised versions of selected papers presented at the the fourth bi-annual international deontic logic conference, DEON’06. There is a substantial introduction (see separate entry), papers from all four invited speakers, David Makinson, Donald Nute, Claudio Pizzi, and Georg Von Wright. After the introduction and lead chapter...

In this paper a new use case for legal argumentation support tools is considered: supporting discussions about analyses of complex criminal cases with the help of Bayesian probability theory. By way of a case study, two actual discussions between experts in court cases are analysed on their argumentation structure. In this study the usefulness of s...

This paper formally compares some central notions from two well-known formalisms for rule-based argumentation, DeLP and ASPIC⁺ . The comparisons especially focus on intuitive adequacy and inter-translatability, consistency, and closure properties. As for differences in the definitions of arguments and attack, it turns out that DeLP ’s definitions a...

This paper formally compares some central notions from two well-known formalisms for rule-based argumentation, DeLP and ASPIC+. The comparisons especially focus on intuitive adequacy and inter-translatability, consistency, and closure properties. As for differences in the definitions of arguments and attack, it turns out that DeLP's definitions are...

Bayesian networks (BNs) are powerful tools that are well-suited for reasoning about the uncertain consequences that can be inferred from evidence. Domain experts, however, typically do not have the expertise to construct BNs and instead resort to using other tools such as argument diagrams and mind maps. Recently, we proposed a structured approach...

Bayesian networks (BNs) are powerful tools that are well-suited for reasoning about the uncertain consequences that can be inferred from evidence. Domain experts, however, typically do not have the expertise to construct BNs and instead resort to using other tools such as argument diagrams and mind maps. Recently, we proposed a struc-tured approach...

Bayesian networks (BNs) are powerful tools that are increasingly being used by forensic and legal experts to reason about the uncertain conclusions that can be inferred from the evidence in a case. Although in BN construction it is good practice to document the model itself, the importance of documenting design decisions has received little attenti...

In this paper a new formal model of argument accrual is proposed as an adaptation of the ASPIC+ framework for structured argumentation. The new model aims to overcome several weaknesses of existing proposals. It is shown to have desirable formal properties that are in line with standard work on formal argumentation, and to be applicable to a range...

In an argumentation approach, legal evidential reasoning is modeled as the construction and attack of “trees of inference” from evidence to conclusions by applying generalizations to evidence or intermediate conclusions. In this paper, an argumentation‐based analysis of the Simonshaven case is given in terms of a logical formalism for argumentation...

In this paper, we propose a structured approach for transforming legal arguments to a Bayesian network (BN) graph. Our approach automatically constructs a fully specified BN graph by exploiting causality information present in legal arguments. Moreover, we demonstrate that causality information in addition provides for constraining some of the prob...

ASPIC⁺ is a general framework for structured argumentation that allows for a considerable degree of freedom as to the knowledge representation choices made in specifying the premises and rules from which arguments are constructed, and the preferences used to determine which attacks amongst constructed arguments succeed as defeats. On the other hand...

This paper builds on the recent ASPIC+ formalism, to develop a general framework for argumentation with preferences. We motivate a revised definition of conflict free sets of arguments, adapt ASPIC+ to accommodate a broader range of instantiating logics, and show that under some assumptions, the resulting framework satisfies key properties and rati...

Recently, a heuristic was proposed for constructing Bayesian networks (BNs) from structured arguments. This heuristic helps domain experts who are accustomed to argumentation to transform their reasoning into a BN and subsequently weigh their case evidence in a probabilistic manner. While the underlying undirected graph of the BN is automatically c...

This chapter discusses how formal models of argumentation can clarify philosophical problems and issues. Some of these arise in the field of epistemology, where it has been argued that the principles by which knowledge can be acquired are defeasible. Other problems and issues originate from the fields of informal logic and argumentation theory, whe...

Recently, a heuristic was proposed for constructing Bayesian networks (BNs) from structured arguments. This heuristic helps domain experts who are accustomed to argumentation to transform their reasoning into a BN and subsequently weigh their case evidence in a probabilis-tic manner. While the underlying undirected graph of the BN is automatically...

The field of computational models of argument is emerging as an important aspect of artificial intelligence research. The reason for this is based on the recognition that if we are to develop robust intelligent systems, then it is imperative that they can handle incomplete and inconsistent information in a way that somehow emulates the way humans t...

Autonomous vehicles are one of the most spectacular recent developments of Artificial Intelligence. Among the problems that still need to be solved before they can fully autonomously participate in traffic is the one of making their behaviour conform to the traffic laws. This paper discusses this problem by way of a case study of Dutch traffic law....

Among the problems that still need to be solved before autonomous vehicles can fully autonomously participate in traffic is the one of making them respect the traffic laws. This paper discusses this problem by way of a case study of Dutch traffic law. First it is discussed to what extent Dutch traffic law exhibits features that are traditionally sa...

In a criminal trial, a judge or jury needs to reason about what happened based on the available evidence, often including statistical evidence. While a probabilistic approach is suitable for analysing the statistical evidence, a judge or jury may be more inclined to use a narrative or argumentative approach when considering the case as a whole. In...

Errors in reasoning about probabilistic evidence can have severe consequences. In the legal domain a number of recent miscarriages of justice emphasises how severe these consequences can be. These cases, in which forensic evidence was misinterpreted, have ignited a scientific debate on how and when probabilistic reasoning can be incorporated in (le...

This paper studies two issues concerning relevance in structured argumentation in the context of the ASPIC+ framework, arising from the combined use of strict and defeasible inference rules. One issue arises if the strict inference rules correspond to classical logic. A longstanding problem is how the trivialising effect of the classical Ex Falso p...

Bayesian networks have gained popularity as a probabilistic tool for reasoning with legal evidence. However, two common difficulties are (1) the construction and (2) the understanding of a network. In previous work, we proposed to use narrative tools and in particular scenario schemes to assist the construction and the understanding of Bayesian net...

Due to the uses of DNA profiling in criminal investigation and decision-making, it is ever more common that probabilistic information is discussed in courts. The people involved have varied backgrounds, as factfinders and lawyers are more trained in the use of non-probabilistic information, while forensic experts handle probabilistic information on...

Qualitative and quantitative systems to deal with uncertainty coexist. Bayesian networks are a well known tool in probabilistic reasoning. For non-statistical experts, however, Bayesian networks may be hard to interpret. Especially since the inner workings of Bayesian networks are complicated they may appear as black box models. Argumentation model...

This article reviews legal applications of logic, arguing that the law is a rich test bed and important application field for logic-based AI research. First applications of logic to the representation of legal regulations are reviewed, where the main emphasis is on representation and where the legal conclusions follow from that representation as a...

In a criminal trial, a judge or jury needs to reach a conclusion about ‘what happened’ based on the available evidence. Often this includes probabilistic evidence. Whereas Bayesian networks form a good tool for analysing evidence probabilistically, simply presenting the outcome of the network to a judge or jury does not allow them to make an inform...

Reasoning about statistics and probabilities can, when not treated with cautiousness, lead to reasoning errors. Over the last decades the rise of forensic sciences has led to an increase in the availability of statistical evidence. To facilitate the correct explanation of such evidence we investigate how argumentation models can help in the interpr...

In order to make an informed decision in a criminal trial, conclusions about what may have happened need to be derived from the available evidence. Recently, Bayesian networks have gained popularity as a probabilistic tool for reasoning with evidence. However, in order to make sense of a conclusion drawn from a Bayesian network, a juror needs to un...

In the academic literature, three approaches to rational legal proof are investigated, broadly speaking based, respectively on Bayesian statistics, on scenario construction and on argumentation. In this article, these approaches are discussed in light of a distinction between direct and indirect probabilistic reasoning. Direct probabilistic reasoni...

In a criminal trial, evidence is used to draw conclusions about what happened concerning a supposed crime. Traditionally, the three main approaches to modeling reasoning with evidence are argumentative, narrative and probabilistic approaches. Integrating these three approaches could arguably enhance the communication between an expert and a judge o...

This article gives a tutorial introduction to the ASPIC + framework for structured argumentation. The philosophical and conceptual underpinnings of ASPIC + are discussed, the main definitions are illustrated with examples and several ways are discussed to instantiate the framework and to reconstruct other approaches as special cases of the framewor...

In abstract argumentation, each argument is regarded as atomic. There is no internal structure to an argument. Also, there is no specification of what is an argument or an attack. They are assumed to be given. This abstract perspective provides many advantages for studying the nature of argumentation, but it does not cover all our needs for underst...

Arguably the significance of an abstract model of argumentation depends on the range of realistic instantiations it allows. This paper therefore investigates for three frameworks for abstract argumentation with support relations whether they can be instantiated with the ASPIC+ framework for structured argumentation. Both evidential argumentation sy...

One tradition in the logical study of argumentation is to allow for arguments that combine strict and defeasible inference rules, and to derive the strict inference rules from a logic at least as strong as classical logic. An unsolved problem in this tradition is how the trivialising effect of the classical Ex Falso principle can be avoided when tw...

This demonstration shows how arguments, formalised in a well defined framework, can be automatically constructed from a given Bayesian network.

Legal reasoning can be approached from various perspectives, traditionally argumentation, probability and narrative. The communication between forensic experts and a judge or jury would benefit from an integration of these approaches. In previous papers we worked on the connection between the narrative and the probabilistic approach. We developed t...

This paper explores the idea that IT security risk assessment can be formalized as an argumentation game in which assessors argue about how the system can be attacked by a threat agent and defended by the assessors. A system architecture plus assumptions about the environment is specified as an ASPIC + argumentation theory, and an argument game is...

In legal cases, stories or scenarios can serve as the context for a crime when reasoning with evidence. In order to develop a scientifically founded technique for evidential reasoning, a method is required for the representation and evaluation of various scenarios in a case. In this paper the probabilistic technique of Bayesian networks is proposed...

Legal cases involve reasoning with evidence and with the development of a software support tool in mind, a formal foundation for evidential reasoning is required. Three approaches to evidential reasoning have been prominent in the literature: argumentation, narrative and probabilistic reasoning. In this paper a combination of the latter two is prop...

Argument schemes can provide a means of explicitly describing reasoning methods in a form that lends itself to computation. The reasoning required to distinguish cases in the manner of CATO has been previously captured as a set of argument schemes. Here we present argument schemes that encapsulate another way of reasoning with cases: using preferen...

In this article we offer a formal account of reasoning with legal cases in terms of argumentation schemes. These schemes, and undercutting attacks associated with them, are formalized as defeasible rules of inference within the ASPIC+ framework. We begin by modelling the style of reasoning with cases developed by Aleven and Ashley in the CATO proje...

In most attempts to model legal systems as formal argumentation systems, legal norms are viewed as an argumentation's system inference rules. Since in formal argumentation systems inference rules are generally assumed to be fixed and independent from the inferences they enable, this approach fails to capture the dialectical connection between norms...

In previous work we presented argumentation schemes to capture the CATO and value based theory construction approaches to reasoning with legal cases with factors. We formalised the schemes with ASPIC+, a formal representation of instantiated argumentation. In ASPIC+ the premises of a scheme may either be a factor provided in a knowledge base or est...

The Argument Interchange Format (AIF) has been devised in order to support the interchange of ideas and data between different projects and applications in the area of computational argumentation. In order to support such interchange, an abstract ontology for argumentation is presented, which serves as an interlingua between various more concrete a...

We provide a retrospective of 25 years of the International Conference on AI and Law, which was first held in 1987. Fifty papers have been selected from the thirteen conferences and each of them is described in a short subsection individually written by one of the 24 authors. These subsections attempt to place the paper discussed in the context of...

Argumentation is the process of supporting claims with grounds and defending them against attack. In the last decades argumentation has become an important topic in philosophy and artificial intelligence. In philosophy, the criticisms of Toul-min and Perelman of formal logic in the 1950s and 1960s gave rise to the field of informal logic, which stu...

Carneades is a recently proposed formalism for structured argumentation with varying proof standards, inspired by legal reasoning, but more generally applicable. Its distinctive feature is that each statement can be given its own proof standard, which is claimed to allow a more natural account of reasoning under burden of proof than existing formal...

John Pollock (1940–2009) was an influential American philosopher who made important contributions to various fields, including epistemology and cognitive science. In the last 25 years of his life, he also contributed to the computational study of defeasible reasoning and practical cognition in artificial intelligence. He developed one of the first...

In this article the argumentation structure of the court’s decision in the Popov v. Hayashi case is formalised in Prakken’s (Argument Comput 1:93–124; 2010) abstract framework for argument-based inference with structured arguments. In this framework, arguments are inference trees formed by applying two kinds of inference rules, strict and defeasibl...

This paper builds on the recent ASPIC+ASPIC+ formalism, to develop a general framework for argumentation with preferences. We motivate a revised definition of conflict free sets of arguments, adapt ASPIC+ASPIC+ to accommodate a broader range of instantiating logics, and show that under some assumptions, the resulting framework satisfies key propert...

Work on argumentation-based dialogue systems often assumes that the adoption of argumentation leads to improved dialogue efficiency and effectiveness. Several studies have taken an experimental approach to prove these alleged benefits, but none has yet supported the expressiveness of a structured argumentation logic. This paper shows how the use of...

This paper discusses two recent developments in the formal study of argumentation-based inference: work on preference-based abstract argumentation and on classical (deductive) argumentation. It is first argued that general models of the use of preferences in argumentation cannot leave the structure of arguments and the nature of attack and defeat u...

The ASPIC + framework is a general framework for argumentation-based inference which aims to unifies two research strands: those in which argu-ments can only be attacked on their defeasible inferences and those in which argu-ments can only be attacked on their premises. The framework is meant to define a wide class of instantiations of abstract arg...

This paper presents a case study in which an opinion of a legal scholar on a legislative proposal is formally reconstructed in the ASPIC+ framework for argumentation-based inference. The reconstruction uses a version of the argument scheme for good and bad consequences that does not refer to single but to sets of consequences, in order to model agg...

Recently resolution of attacks has been studied in the context of abstract argumentation frameworks. In this paper it is claimed that resolutions should be studied under the assumption that they are generated through the acquisition of preference information, and that this implies that the existing study of resolutions has limited applicability. A...

Increasingly research into the uses of argumentation in multi- agent dialogues takes an experimental approach. Such studies explore how agents can successfully employ argumentation besides the best and worst case situations of formal analysis. While a vital part in these ex- periments is influenced by the scenarios from which dialogues are gen- era...

A formal two-phase model of democratic policy deliberation is presented, in which in the first phase sufficient and necessary criteria for proposals to be accepted are determined (the `acceptable' criteria) and in the second phase proposals are made and evaluated in light of the acceptable criteria resulting from the first phase. Such a separation...

The main goal of a persuasion dialogue is to persuade, but agents may have a number of additional goals concerning the dialogue duration, how much and what information is shared or how aggressive the agent is. Several criteria have been proposed in the literature covering different aspects of what may matter to an agent, but it is not clear how to...

A well-known ambiguity in the term ‘argument’ is that of argument as an inferential structure and argument as a kind of dialogue. In the first sense, an argument is a structure with a conclusion supported by one or more grounds, which may or may not be supported by further grounds. Rules for the construction and criteria for the quality of argument...

The ASPIC+ framework is intermediate in abstraction between Dung's argumentation framework and concrete instantiating logics. This paper generalises ASPIC+ to accommodate classical logic instantiations, and adopts a new proposal for evaluating extensions: attacks are used to define the notion of conflict-free sets, while the defeats obtained by app...

Carneades is a recently proposed formalism for structured argumentation with varying proof standards. An open question is its relation with Dung's seminal abstract approach to argumentation. In this paper the two formalisms are formally related by translating Carneades into ASPIC+, another recently proposed formalism for structured argumentation. S...

A formal model is proposed of argumentation with burdens and standards of proof, overcoming shortcomings of earlier work. The model is based on a distinction between default and inverted burdens of proof. This distinction is formalised by adapting the definition of defeat of the ASPIC+ framework for structured argumentation. Since ASPIC+ generates...

This paper investigates the modelling of burden of proof in AI & law models of legal argument. The main topic is how allocations of burden of proof determine the required strength of counterarguments. It is argued that the two currently available approaches both have some shortcomings. On the one hand, techniques for modelling burden of proof in no...

The starting point of this article is the claim that logics for defeasible argumentation provide the means to logically characterise the difference between several kinds of proof burdens, but only if they are embedded in a dynamic setting that captures the various stages of a legal proceeding. It is also argued that ëstandardí argumentation logics...

This paper studies the use of hypothetical and value-based reasoning in US Supreme-Court cases concerning the United States Fourth Amendment. Drawing upon formal AI & Law models of legal argument a semi-formal reconstruction is given of parts of the Carney case, which has been studied previously in AI & law research on case-based reasoning. As par...

This paper presents a theory of reasoning with evidence in order to determine the facts in a criminal case. The focus is on the process of proof, in which the facts of the case are determined, rather than on related legal issues, such as the admissibility of evidence. In the literature, two approaches to reasoning with evidence can be distinguished...

An abstract framework for structured arguments is presented, which instantiates Dung's (‘On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming, and n-Person Games’, Artificial Intelligence, 77, 321–357) abstract argumentation frameworks. Arguments are defined as inference trees formed by applying tw...

Agents engage in deliberation dialogues to collectively decide on a course of action. To solve conflicts of opinion that arise, they can question claims and supply arguments. Existing models fail to capture the interplay between the provided arguments as well as successively selecting a winner from the proposals. This paper introduces a general fra...

The Association for the Advancement of Artificial Intelligence was pleased to present the 2009 Fall Symposium Series, held Thursday through Saturday, November 5–7, at the Westin Arlington Gateway in Arlington, Virginia. The Symposium Series was preceded on Wednesday, November 4 by a one-day AI funding seminar. The titles of the seven symposia were...

A formal two-phase model of democratic policy deliberation is presented, in which in the first phase sufficient and necessary criteria for proposals to be accepted are determined (the 'admissible' criteria') and in the second phase proposals are made and evaluated in light of the admissible criteria resulting from the first phase. Argument schemes...

In order to support the interchange of ideas and data between different projects and applications in the area of computational argumentation, a common ontology for computational argument, the Argument Interchange Format (AIF), has been devised. One of the criticisms levelled at the AIF has been that it does not take into account formal argumentatio...