This article discusses agent-based simulation (ABS) as a tool of sociological understanding. I argue that agent-based simulations can play an important role in the expansion of explanatory understanding in the social sciences. The argument is based on an inferential account of understanding (Ylikoski 2009, Ylikoski & Kuorikoski 2010), according to which computer simulations increase our explanatory understanding by expanding our ability to make what-if inferences about social processes and by making these inferences more reliable. The inferential account also (...) suggests a number of ways in which the use of simulation methodology might give rise to illusory understanding. The structure of the article is as .. (shrink)

Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition, strategic interaction, collective learning, and the possibility of multiple equilibria. Recent advances in analytical and computational tools are permitting new approaches to the quantitative study of these aspects. One such approach is Agent-based Computational Economics (ACE), the computational study of economic processes modeled as (...) dynamic systems of interacting agents. This chapter explores the potential advantages and disadvantages of ACE for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, institutional arrangements, and behavioral dispositions. (shrink)

Agent-based accounts of virtue ethics, such as the one provided by Michael Slote, base the rightness of action in the motive from which it proceeds. A frequent objection to agent-basing is that it does not allow us to draw the commonsense distinction between doing the right thing and doing it for the right reasons, that is, between act-evaluation and agent-appraisal. I defend agent-basing against this objection, but argue that a more fundamental problem for this (...) account is its apparent failure to provide adequate argue action guidance. I then show that this problem can be solved by supplementing an agent-based criterion of right action with a hypothetical-agent criterion of action guidance. (shrink)

This article describes the potential impact that free (i.e., open source) software can have on an existing commercial software market. A model for the software market is constructed in terms of autonomous agents, which represent the users, the companies, and the free software providers. The model specifies a reservation price for each user agent and develops a gradient learning strategy for revenue-maximizing company agents. Simulations explore parameters such as the demand distribution, and the relative importance of market share, advertising (...) and random effects in product visibility. Results from the case without free software show a prevalence of monopolies, which is consistent with other studies of high-technology market economics. The effects of free software are not uniform, but are highly parameter dependent. A “capture region” is found in which free software eventually dominates the market. (shrink)

In this paper, we present an agent-based model for studying the impact of 'myside bias' on the argumentative dynamics in scientific communities. Recent insights in cognitive science suggest that scientific reasoning is influenced by `myside bias'. This bias manifests as a tendency to prioritize the search and generation of arguments that support one's views rather than arguments that undermine them. Additionally, individuals tend to apply more critical scrutiny to opposing stances than to their own. Although myside bias may pull (...) individual scientists away from the truth, its effects on communities of reasoners remain unclear. The aim of our model is two-fold: first, to study the argumentative dynamics generated by myside bias, and second, to explore which mechanisms may act as a mitigating factor against its pernicious effects. Our results indicate that biased communities are epistemically less successful than non-biased ones, and that they also tend to be less polarized than non-biased ones. Moreover, we find that two socio-epistemic mechanisms help communities to mitigate the effect of the bias: the presence of a common filter on weak arguments, which can be interpreted as shared beliefs, and an equal distribution of agents for each alternative at the beginning. (shrink)

According to agent-based approaches to virtue ethics, the rightness of an action is a function of the motives which prompted that action. If those motives were morally praiseworthy, then the action was right; if they were morally blameworthy, the action was wrong. Many critics find this approach problematically insensitive to an act’s consequences, and claim that agent-basing fails to preserve the intuitive distinction between agent- and act-evaluation. In this article I show how an agent-based account (...) of right action can be made sensitive to an act’s consequences. According to the approach which I defend, an action is right just in case it realizes an agent’s morally praiseworthy motive. Conversely, an action is wrong just in case it realizes a morally blameworthy motive. Specifying act-evaluation in terms of the realization, rather than the expression, of an agent’s motives allows an agent-based approach to distinguish between agent- and act-evaluation. This is because an agent may act from a morally praiseworthy motive, but fail to realize that motive. Her action will therefore not have been the right one, despite its being the expression of morally praiseworthy motives. (shrink)

Abstract Agent-based virtue ethics is a unitary normative theory according to which the moral status of actions is entirely dependent upon the moral status of an agent's motives and character traits. One of the problems any such approach faces is to capture the common-sense distinction between an agent's doing the right thing, and her doing it for the right (or wrong) reason. In this paper I argue that agent-based virtue ethics ultimately fails to capture this kind (...) of fine-grained distinction, and to this extent ought to be rejected. I focus first on Michael Slote's agent-based theory, according to which the moral status of actions depends upon an agent's actual motives, and argue that this leads to a paradox. I then consider whether the ?counterfactual? version of agent-basing favoured by Rosalind Hursthouse and Linda Zagzebski fares any better, and conclude that it does not. (shrink)

I argue for an intentional conception of representation in science that requires bringing scientific agents and their intentions into the picture. So the formula is: Agents (1) intend; (2) to use model, M; (3) to represent a part of the world, W; (4) for some purpose, P. This conception legitimates using similarity as the basic relationship between models and the world. Moreover, since just about anything can be used to represent anything else, there can be no unified ontology of models. (...) This whole approach is further supported by a brief exposition of some recent work in cognitive, or usage-based, linguistics. Finally, with all the above as background, I criticize the recently much discussed idea that claims involving scientific models are really fictions. (shrink)

Agent-​​based modeling is showing great promise in the social sciences. However, two misconceptions about the relation between social macroproperties and microproperties afflict agent-based models. These lead current models to systematically ignore factors relevant to the properties they intend to model, and to overlook a wide range of model designs. Correcting for these brings painful trade-​​offs, but has the potential to transform the utility of such models.

This study provides a basic introduction to agent-based modeling (ABM) as a powerful blend of classical and constructive mathematics, with a primary focus on its applicability for social science research. The typical goals of ABM social science researchers are discussed along with the culture-dish nature of their computer experiments. The applicability of ABM for science more generally is also considered, with special attention to physics. Finally, two distinct types of ABM applications are summarized in order to illustrate concretely the (...) duality of ABM: Real-world systems can not only be simulated with verisimilitude using ABM; they can also be efficiently and robustly designed and constructed on the basis of ABM principles. (shrink)

Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, section 2 (...) gives conceptual tools to explain the rationale of the diverse epistemological positions presented in section 1. Finally, we claim that a careful attention to the real multiplicity of denotational powers of symbols at stake and then to the implicit routes of references operated by models and computer simulations is necessary to determine, in each case, the proper epistemic status and credibility of a given model and/or simulation. (shrink)

This book brings together contributions from leading researchers in the field of agent-based modelling and simulation. This approach has grown out of some recent and innovative ideas in the social sciences, computer sciences, life sciences, physics and game theory. It is proving helpful in understanding complexity in many domains. The opportunities it offers to explore the experimental approach to social and human behaviour is proving of theoretical and empirical value across a wide range of fields. With contributions from researchers (...) whose work has served to define this new field such as Nigel Gilbert, Robert Axtell (in economics and social science) and Jacques Ferber (in multi-agent systems), as well as practitioners who are working at the cutting edge of the new domain, this collection of essays has been assembled by two of its leading exponents: Frédéric Amblard and Denis Phan. The research, case studies and theoretical approaches discussed in this book are designed to introduce beginners and experts alike to the current state of play in this new and exciting field of social science. (shrink)

This volume brings together contributions from leading researchers in the field of agent-based modelling and simulation. This approach has grown out of some recent and innovative ideas in the social sciences, computer sciences, life sciences, physics and game theory. It is proving helpful in understanding complexity in many domains. The opportunities it offers to explore the experimental approach to social and human behaviour is proving of theoretical and empirical value across a wide range of fields. With contributions from researchers (...) whose work has served to define this new field such as Nigel Gilbert, Robert Axtell (in economics and social science) and Jacques Ferber (in multi-agent systems), as well as practitioners who are working at the cutting edge of the new domain, this collection of essays has been assembled by two of its leading exponents: Frédéric Amblard and Denis Phan. The research, case studies and theoretical approaches discussed in this book are designed to introduce beginners and experts alike to the current state of play in this new and exciting field of social science. (shrink)

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still (...) a need for methods that bridge the gap between spatially‐detailed and computationally‐efficient approaches. In this review, we summarize the capabilities of agent‐based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. (shrink)

Agent-based modeling has become a common and well-established tool in the social sciences and certain of the humanities. Here, we aim to provide an overview of the different modeling approaches in current use. Our discussion unfolds in two parts: we first classify different aspects of the model-building process and identify a number of characteristics shared by most agent-based models in the humanities and social sciences; then we map relevant differences between the various modeling approaches. We classify these into (...) different dimensions including the type of target systems addressed, the intended modeling goals, and the models’ degree of abstraction. Along the way, we provide reference to related debates in contemporary philosophy of science. (shrink)

Agent-based virtue ethics strives to offer a viable account of both moral conduct and the source of moral value, independent of ‘deontic’ teleological and deontological characterizations. One of its chief proponents offers an agent-based virtue-ethical account that aspires to derive all moral value, including the moral status of actions, solely from the ‘aretaic’ concept of benevolence.I suggest that morality as benevolence fails to offer a viable account of either virtuous moral conduct or the source of moral value, because (...) it is selfundermining in both respects. In order to solve this structural problem, it appears as if the theory may have to give up its agent-based status. (shrink)

In Morals From Motives, Michael Slote defends an agent-based theory of right action according to which right acts are those that express virtuous motives like benevolence or care. Critics have claimed that Slote’s view— and agent-based views more generally— cannot account for several basic tenets of commonsense morality. In particular, the critics maintain that agent-based theories: (i) violate the deontic axiom that ought implies can , (ii) cannot allow for a person’s doing the right thing for the (...) wrong reason, and (iii) do not yield clear verdicts in a number of cases involving conflicting motives and motivational over-determination . In this paper I develop a new agent-based theory of right action designed to avoid the problems presented for Slote’s view. This view makes morally right action a matter of expressing an optimal balance of virtue over vice and commands agents in each situation to improve their degree of excellence to the greatest extent possible. (shrink)

In this paper, I develop an objection to agent-based accounts of right action. Agent-based accounts of right action attempt to derive moral judgment of actions from judgment of the inner quality of virtuous agents and virtuous agency. A moral theory ought to be something that moral agents can permissibly use in moral deliberation. I argue for a principle that captures this intuition and show that, for a broad range of other-directed virtues and motives, agent-based accounts of right (...) action fail to satisfy this principle. (shrink)

Agent-based models (ABMs) are one type of simulation model used in the context of the COVID-19 pandemic. In contrast to equation-based models, ABMs are algorithms that use individual agents and attribute changing characteristics to each one, multiple times during multiple iterations over time. This paper focuses on three philosophical aspects of ABMs as models of causal mechanisms, as generators of emergent phenomena, and as providers of explanation. Based on my discussion, I conclude that while ABMs cannot help much with (...) causal inference, they can be viewed as etio-prognostic explanations of illness occurrence and outcome. (shrink)

Frigg and Reiss (2009) argue that philosophical problems in simulation bear enough resemblance to recognized issues in the philosophy of modeling that they only pose challenges analogous to those found in standard analytic models used to represent natural systems. They suggest that there are no new philosophical problems in computer simulation modeling beyond those found in traditional mathematical modeling. Winsberg (2009) has countered that there appear to be genuinely new epistemological problems in simulation modeling because the knowledge obtained from them (...) is ‘downward, motley, and autonomous.’ Here I draw out some specific ways that these epistemological problems are manifest in complex ecological simulation, especially in agent-based models. These models contain novel features that were impossible to anticipate prior to the computer revolution, and continue to present difficulties and challenges of both a practical and philosophical nature (Humphreys 2002). (shrink)

Agent-Based Models are useful to describe and understand social, economic and spatial systems' dynamics. But, beside the facilities which this methodology offers, evaluation and comparison of simulation models are sometimes problematic. A rigorous conceptual frame needs to be developed. This is in order to ensure the coherence in the chain linking at the one extreme the scientist's hypotheses about the modeled phenomenon and at the other the structure of rules in the computer program. This also systematizes the model design (...) from the thematician conceptual framework as well. The aim is to reflect upon the role that a well defined ontology, based on the crossing of the philosophical and the computer science insights, can play to solve such questions and help the model building. We analyze different conceptions of ontology, introduce the 'ontological test' and show its usefulness to compare models. Then we focus on the model building and show the place of a systematic ABM ontology. The latter process is situated within a larger framework called the 'knowledge framework' in which not only the ontologies but also the notions of theory, model and empirical data take place. At last the relation between emergence and ontology is discussed. (shrink)

The article presents an agent-based model of scientific interaction aimed at examining how different degrees of connectedness of scientists impact their efficiency in knowledge acquisition. The model is built on the basis of Zollman’s ABM by changing some of its idealizing assumptions that concern the representation of the central notions underlying the model: epistemic success of the rivalling scientific theories, scientific interaction and the assessment in view of which scientists choose theories to work on. Our results suggest that whether (...) and to what extent the degree of connectedness of a scientific community impacts its efficiency is a highly context-dependent matter since different conditions deem strikingly different results. More generally, we argue that simplicity of ABMs may come at a price: the requirement to run extensive robustness analysis before we can specify the adequate target phenomenon of the model.1 1Introduction2Zollman's 2010 Model3Static versus Dynamic Epistemic Success 3.1Introducing the notion of dynamic epistemic success3.2Implementation and results for the basic setup4Critical Interaction 4.1Introducing critique4.2Implementation and results5Inertia of Inquiry 5.1Introducing rational inertia5.2Implementation and results6Threshold Below Which Theories Are Equally Promising 6.1An inquiry that is even more difficult6.2Implementation and results7Discussion8Conclusion. (shrink)

In Morals from Motives (2001) Michael Slote puts forward an agent-based virtue ethics that purports to derive an account of deontic terms from aretaic evaluations of motives or character traits. In this view, an action is right if and only if it proceeds from a good or virtuous motive or at least does not come from a bad motive, and wrong if it comes from a bad motive. I argue that Slote does not provide an account of right action (...) at all, that is, if ‘right action’ is understood in the strict deontic sense of an act that is either permissible or obligatory. An examination of Slote’s treatment of the problem of moral luck shows that he presupposes a conceptual link between what is morally wrong and what is blameworthy. I conclude by suggesting that agent-based virtue ethics may do better as an attempt to eliminate deontic notions altogether. (shrink)

Scientists and engineers seek to understand how real-world systems work and could work better. Any modeling method devised for such purposes must simplify reality. Ideally, however, the modeling method should be flexible as well as logically rigorous; it should permit model simplifications to be appropriately tailored for the specific purpose at hand. Flexibility and logical rigor have been the two key goals motivating the development of Agent-based Computational Economics (ACE), a completely agent-based modeling method characterized by seven specific (...) modeling principles. This perspective provides an overview of ACE, a brief history of its development, and its role within a broader spectrum of experiment-based modeling methods. (shrink)

Some issues and varieties of computational and other approaches to understanding socially embedded phenomena are discussed. It is argued that of all the approaches currently available, only agent-based simulation holds out the prospect for adequately representing and understanding phenomena such as social norms.

The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. We review the literature regarding agent-based economics, disruptive innovation, and transition management and determine the following requirements. Actors must be detailed, heterogeneous, (...) interacting, learning, and strategizing. Technology should be represented as a detailed and heterogeneous portfolio that can develop in a bottom-up manner, using endogenous feedback loops. Assumptions about discount rates and the social cost of carbon should be configurable. The model should contain interactions between the global, national, local, and individual level. A review of modelling techniques shows that equilibrium models are unsuitable and that system dynamics and discrete event simulation are too limited. The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled. But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within the agent-based framework. We conclude with practical guidelines. (shrink)

This article proposes the use of agent-based simulation to analyze complex design trade-offs that involve value tensions. This is illustrated by a case study in the domain of train traffic control. In this case, agent-based simulation supported the involvement of stakeholders and increased understanding of a design trade-off.

In a digital communication environment, information security is mandatory. Three essential parameters used in the design process of a steganography algorithm are Payload, security, and fidelity. However, several methods are implemented in information hiding, such as Least Significant Bit (LBS), Discrete Wavelet Transform, Masking, and Discrete Cosine Transform. The paper aims to investigate novel steganography techniques based on agent technology. It proposes a Framework of Steganography based on agent for secret communication using LSB. The most common image steganography (...) databases are explored for training and testing. The methodology in this work is based on the statistical properties of the developed agent software using Matlab. The experiment design is based on six statistical feature measures, including Histogram, Mean, Standard deviation, Entropy, Variance and Energy. For steganography, an Ensemble classifier is used to test two scenarios: embedding a single language message and inserting bilingual messages. ROC Curve represents the evaluation metrics. The result shows that the designed agent-based system with 50% training/testing sample set and 0.2 Payload can pick out the best cover image for the provided hidden message size to avoid visual artifact. (shrink)

Agent-based models have played a prominent role in recent debates about the merits of democracy. In particular, the formal model of Lu Hong and Scott Page and the associated “diversity trumps ability” result has typically been seen to support the epistemic virtues of democracy over epistocracy (i.e., governance by experts). In this paper we first identify the modeling choices embodied in the original formal model and then critique the application of the Hong-Page results to philosophical debates on the relative (...) merits of democracy. In particular we argue that the “best-performing agents” in Hong-Page model should not be interpreted as experts. We next explore a closely related model in which best-performing agents are more plausibly seen as experts and show that the diversity trumps ability result fails to hold. However, with changes in other parameters (such as the deliberation dynamic) the diversity trumps ability result is restored. The sensitivity of this result to parameter choices illustrates the complexity of the link between formal modeling and more general philosophical claims; we use this debate as a platform for a more general discussion of when and how agent-based models can contribute to philosophical discussions. (shrink)

A crisis continues to brew within the pharmaceutical research and development (R&D) enterprise: productivity continues declining as costs rise, despite ongoing, often dramatic scientific and technical advances. To reverse this trend, we offer various suggestions for both the expansion and broader adoption of modeling and simulation (M&S) methods. We suggest strategies and scenarios intended to enable new M&S use cases that directly engage R&D knowledge generation and build actionable mechanistic insight, thereby opening the door to enhanced productivity. What M&S requirements (...) must be satisfied to access and open the door, and begin reversing the productivity decline? Can current methods and tools fulfill the requirements, or are new methods necessary? We draw on the relevant, recent literature to provide and explore answers. In so doing, we identify essential, key roles for agent-based and other methods. We assemble a list of requirements necessary for M&S to meet the diverse needs distilled from a collection of research, review, and opinion articles. We argue that to realize its full potential, M&S should be actualized within a larger information technology framework—a dynamic knowledge repository—wherein models of various types execute, evolve, and increase in accuracy over time. We offer some details of the issues that must be addressed for such a repository to accrue the capabilities needed to reverse the productivity decline. (shrink)

Practical reason or rationality can be understood in agent‐based terms. Strength of purpose, for example, can be internally characterized, and the rationality of the courage to face facts and not deceive oneself about what is unpleasant or horrifying can also be understood in agent‐based terms. Practical rationality also requires us not to be self‐defeatingly insatiable in our wants, but this likewise is a feature of inner motivation. Finally, being rational seems to require a certain amount of concern for (...) one's own well‐being or happiness – just as being moral requires a certain kind of concern for others; but like the other conditions of practical rationality just mentioned, this kind of concern can readily be understood in agent‐based terms. In fact, it makes more intuitive sense to understand the rationality of self‐interest in terms of motivation than to understand it in terms of consequences. (shrink)

Using agent‐based modelling, Harrington, Kleber, Reubold, Schiel & Stevens (2018) develop a unified model of sound change based on cognitive processing of human speech and theories of how social factors constrain the spread of change throughout a community. They conclude that many types of change result from how biases in the phonetic distribution of phonological categories are transmitted via accommodation processes between individuals in interaction.

This article aims at contributing to the discussion about the relationships between ICT, computer science and policy-making by focusing on agent-based social simulation. Enabled, from a technical point of view, by the developments of Distributed Artificial Intelligence in the 1990s and by the features of the object-oriented programming paradigm, agent-based social simulations are a tool for the analysis of social dynamics that can be used also to support the design and the evaluation of public policies. After a brief (...) description of social simulation paradigm and of its impact on social sciences, the paper presents a simple agent-based model devised to analyze, even if in a very abstract way, a phenomenon that can rouse the interest of legal scientists: the interplay between damaging behaviors, punishment and social mechanisms of learning and imitation. Our goal is to show how agent-based simulation can be used not only to illuminate basic mechanisms underlying social phenomena but also to reflect, in an innovative way, on how society can deal with them. (shrink)

Herein is provided a brief overview of agent-based modeling , with a particular slant toward its potential as a tool for the theoretical biologist. Of course, its use for experimentalists is obvious; they are, as a group, already using agent-based models to examine contemporary biological questions ranging from molecular processes to evolving ecological landscapes . For the modeler-theoretician, ABMs offer a new tool for thinking about the structure of biological processes, thus creating a conduit for integrative perspective taking (...) between the experimentalist and the theoretician. (shrink)

Philosophy Compass, Volume 17, Issue 7, July 2022.

This paper argues against the priority of pure, virtue-based accounts of argumentative norms [VA]. Such accounts are agent-based and committed to the priority thesis: good arguments and arguing well are explained in terms of some prior notion of the virtuous arguer arguing virtuously. Two problems with the priority thesis are identified. First, the definitional problem: virtuous arguers arguing virtuously are neither sufficient nor necessary for good arguments. Second, the priority problem: the goodness of arguments is not explained virtuistically. Instead, (...) being excellences, virtues are instrumental in relation to other, non-aretaic goods—in this case, reason and rationality. Virtues neither constitute reasons nor explain their goodness. Two options remain for VA: either provide some account of reason and rationality in virtuistic terms, or accept them as given but non-aretaic goods. The latter option, though more viable, demands the concession that VA cannot provide the core norms of argumentation theory. (shrink)

In this paper I examine the epistemic function of agent-based models of scientific inquiry, proposed in the recent philosophical literature. In view of Boero and Squazzoni’s classification of ABMs into case-based models, typifications and theoretical abstractions, I argue that proposed ABMs of scientific inquiry largely belong to the last category. While this means that their function is primarily exploratory, I suggest that they are epistemically valuable not only as a temporary stage in the development of ABMs of science, but (...) by providing insights into theoretical aspects of scientific rationality. I illustrate my point with two examples of highly idealized ABMs of science, which perform two exploratory functions: Zollman’s ABM which provides a proof-of-possibility in the realm of theoretical discussions on scientific rationality, and an argumentation-based ABM, which provides insights into potential mechanisms underlying the efficiency of scientific inquiry. (shrink)

Scientific research that could cause grave harm, either through accident or intentional malevolence, is known as dual-use research. Recent high-profile cases of dual-use research in the life sciences have led to debate about the extent to which restrictions on the conduct and dissemination of such research may impede scientific progress. We adapt formal models of scientific networks to systematically explore the effects that different regulatory schemes may have on a community’s ability to learn about the world. Our results suggest that, (...) contrary to common wisdom, some restrictions on the conduct and dissemination of dual-use research do not inhibit scientific progress and may actually aid communities in learning. (shrink)

According to an influential characterisation of reflective equilibrium, it is a kind of algorithm for licensing explicitly normative claims in philosophical inquiries. Call this the machine-view of reflective equilibrium. The machine-view implies a causal relation between input and output data that is devoid of human agency in any significant sense. In this paper, I argue for a neo-Aristotelian alternative view. According to this view, the judgement that is called forth in the decision procedure of reflective equilibrium is a rational response (...) of an epistemic agent, which integrates the whole of her character as a knower, both cognitive and affective, and which cannot be reduced to the explicit following of rules or an algorithm. Unlike the machine-view, this alternative account is able to support the dynamic structure and the normative status of the decision procedure. (shrink)

In ‘Against agent-based virtue ethics' (2004) Michael Brady rejects agent-based virtue ethics on the grounds that it fails to capture the commonsense distinction between an agent's doing the right thing, and her doing it for the right reason. In his view, the failure to account for this distinction has paradoxical results, making it unable to explain why an agent has a duty to perform a given action. I argue that Brady's objection relies on the assumption that (...) an agent-based account is committed to defining obligations in terms of actual motives. If we reject this view, and instead provide a version of agent-basing that determines obligations in terms of the motives of the hypothetical virtuous agent, the paradox disappears. (shrink)