Intentionality in Interaction revisits some of the classical questions to be found in the original programme for second-personal studies as established in Thompson's 2001 JCS issue and sheds new light on them, witnessing the evolving dynamics of such a programme over the last decade. The contributions in this issue approach the questions of how persons share intentions, emotions, and experiences, of how interaction is shaped by and transforms affection, emotion, and cognition, and of how such interactions develop over time and (...) provide important insights into the development of human capacities in general, both in normal and pathological cases. In this introduction, we situate the special issue in the context of social cognition in general and second-personal studies in particular. We propose an outline of a new framework to approach questions regarding interaction and its development and evolution, a framework based on a novel understanding of interaction in terms of engagement between persons. (shrink)

This paper studies the complexity of behavior of multi-agent systems. Behavior properties are formulated using classical temporal logic languages and are checked with respect to the transition system induced by the definition of the multi-agent system. We establish various tight complexity bounds of the behavior properties under natural structural and semantic restrictions on agent programs and actions.

The construction of complex simulation models and the application of new computer hardware to ecological problems has resulted in the need for many ecologists to rely on computer programmers to develop their modelling software. However, this can lead to a lack of flexibility and understanding in model implementation and in resource problems for researchers. This paper presents a new programming language, Viola, based on a simple organisational concept which can be used by most researchers to develop complex simulations much more (...) easily than could be achieved with standard programming languages such as C++. The language is object oriented and implemented through a visual interface. It is specifically designed to cope with complicated individual based behavioural simulations and comes with embedded concurrency handling abilities. (shrink)

In the paper, the touchstone points of the project “Towards an agency-based philosophy of (advanced) technology” are outlined. The main plot of this elaboration concerns human-machine interactions and appropriate interpretation of reciprocal aligning, adapting within involved into such interactions agents; as well as the status as such of being an agent. Into the theoretical and historical background of the project such spheres as Philosophy of Science, Philosophy of Technology, Philosophy of Engineering and Design Technological Actions, STS (Science and Technology (...) Studies), Applied Ethics etc. could be invited. To treat agency as technology, reestablish the role of agency in technology is the most ambitious goal of the project: ‘activity as technology’ focuses on activities through technologies. The terms «agency» and «activity» are used in this paper synonymously with the basic Aristotelian meaning of agent’s potential capacity to act. The proposed by the author theory of action and agency (and correspondently defended in 2016 dissertation of Doctor of Philosophical Science) is to be applied into philosophical reflections about various problems of dealing with currently continually appearing flourishing fields of artificial intelligence, machine learning (including deep learning methods and simulation methods), inventing computers and codes, numerically controlled machines and robots, computer-chip equipped devices, smart objects etc. (shrink)

In the past decade, the fields of machine learning and artificial intelligence (AI) have seen unprecedented developments that raise human-machine interactions (HMI) to the next level.Smart machines, i.e., machines endowed with artificially intelligent systems, have lost their character as mere instruments. This, at least, seems to be the case if one considers how humans experience their interactions with them. Smart machines are construed to serve complex functions involving increasing degrees of freedom, and they generate solutions not fully anticipated by humans. (...) Consequently, their performances show a touch of action and even autonomy. HMI is therefore often described as a sort of “cooperation” rather than as a mere application of a tool. Some authors even go as far as subsuming cooperation with smart machines under the label ofpartnership, akin to cooperation between human agents sharing a common goal. In this paper, we explore how far the notion of shared agency and partnership can take us in our understanding of human interaction with smart machines. Discussing different topoi related to partnerships in general, we suggest that different kinds of “partnership” depending on the form of interaction between agents need to be kept apart. Building upon these discussions, we propose a tentative taxonomy of different kinds of HMI distinguishing coordination, collaboration, cooperation, and social partnership. (shrink)

Despite their diversity, human languages share consistent properties and regularities. Wherefrom does this consistency arise? And does it tell us something about the problem that all languages need to solve? The authors provide an intriguing analyses which focuses on the “communicative function of ambiguity” whose resolution entailed an equally intriguing “speaker–listener cross‐entropy objective for measuring the efficiency of linguistic systems from first principles of efficient language use.”.

This books offers a naturalistic and critical theory of signs, minds, and meaning-in-the-world.

Interactions between an intelligent software agent and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user’s access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by goals, make autonomous decisions, and can learn from experience. Using ideas from bounded rationality, we frame these interactions (...) as instances of an ISA whose reward depends on actions performed by the user. Such agents benefit by steering the user’s behaviour towards outcomes that maximise the ISA’s utility, which may or may not be aligned with that of the user. Video games, news recommendation aggregation engines, and fitness trackers can all be instances of this general case. Our analysis facilitates distinguishing various subcases of interaction, as well as second-order effects that might include the possibility for adaptive interfaces to induce behavioural addiction, and/or change in user belief. We present these types of interaction within a conceptual framework, and review current examples of persuasive technologies and the issues that arise from their use. We argue that the nature of the feedback commonly used by learning agents to update their models and subsequent decisions could steer the behaviour of human users away from what benefits them, and in a direction that can undermine autonomy and cause further disparity between actions and goals as exemplified by addictive and compulsive behaviour. We discuss some of the ethical, social and legal implications of this technology and argue that it can sometimes exploit and reinforce weaknesses in human beings. (shrink)

In this paper, we present a formal interpretive account of Jean Piaget’s theory of the morality that regulates social exchanges, which we call interactional morality. First, we place Piaget’s conception in the context of his epistemological and sociological works. Then, we review the core of that conception: the two types of interactional moralities that Piaget identified to be usual in social exchanges, and the role that the notion of respect-for-the-other plays in their definition. Next, we analyze the main features of (...) social exchanges that are subject to each of those two types of interactional moralities. Following, we formalize Piaget’s account of how the two types of interactional moralities can be put to regulate social exchanges in which values, norms, beliefs, and goals are exchanged, so that interactional commitments can be established among the participants. Then, we sketch a moral reasoning system able to support formal reasonings about interactional moralities. Finally, we illustrate the usefulness of the overall formal model of interactional moralities that resulted from our study by applying it to the explication of some of the conclusions achieved by Piaget in his moral studies about children games. (shrink)

Advances in artificial intelligence (AI) create an increasing similarity between the performance of AI systems or AI-based robots and human communication. They raise the questions: whether it is possible to communicate with, understand, and even empathically perceive artificial agents; whether we should ascribe actual subjectivity and thus quasi-personal status to them beyond a certain level of simulation; what will be the impact of an increasing dissolution of the distinction between simulated and real encounters. (1) To answer these questions, the (...) paper argues that the precondition for actually understanding others consists in the implicit assumption of the subjectivity of our counterpart, which makes shared feelings and a „we-intentionality” possible. This assumption is ultimately based on the presupposition of a shared form of life, conceived here as „conviviality.” (2) The possibility that future artificial agents could meet these preconditions is refuted on the basis of embodied and enactive cognition, which links subjectivity and consciousness to the aliveness of an organism. (3) Even if subjectivity is in principle impossible for artificial agents, the distinction between simulated and real subjectivity might nevertheless become increasingly blurred. Here, possible consequences are discussed, especially using the example of virtual psychotherapy. Finally, the paper makes case for a mindful appproach to the language we use to talk about artificial systems and pleads for preventing a systematic pretense of subjectivity. (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)

Diversity of agents occurs naturally in epistemic logic, and dynamic logics of information update and belief revision. In this paper we provide a systematic discussion of different sources of diversity, such as introspection ability, powers of observation, memory capacity, and revision policies, and we show how these can be encoded in dynamic epistemic logics allowing for individual variation among agents. Next, we explore the interaction of diverse agents by looking at some concrete scenarios of communication and learning, (...) and we propose a logical methodology to deal with these as well. We conclude with some further questions on the logic of diversity and interaction. (shrink)

Numerous research groups around the world are attempting to build realistic and believable autonomous embodied agents that attempt to have natural interactions with users. Research into these entities has primarily focused on their potential to enhance human–computer interaction. As a result, there is little understanding of the potential for embodied entities to abuse and manipulate users for questionable purposes. We highlight the potential opportunities for abuse when interacting with embodied agents in virtual worlds and discuss how our (...) social interactions with such entities can contribute to abusive behaviour. Suggestions for reducing such risks are also provided, along with suggestions for important future research areas. (shrink)

We model differences among agents in their ability to recognize temporal patterns of prices. Using the concept of DeBruijn sequences in two dynamic models of markets, we demonstrate the existence of equilibria in which prices fluctuate in a pattern that is independent of the fundamentals and that can be recognized only by the more competent agents. (JEL: C7, D4.

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

This paper considers a new class of agent dynamic logics which provide a formal means of specifying and reasoning about the agents activities and informational, motivational and practical aspects of the behaviour of the agents. We present a Hilbert-style deductive system for a basic agent dynamic logic and consider a number of extensions of this logic with axiom schemata formalising interactions between knowledge and commitment (expressing an agent s awareness of her commitments), and interactions between knowledge and actions (...) (expressing no learning and persistence of knowledge after actions). The deductive systems are proved sound and complete with respect to a Kripke-style semantics. Each of the considered logics is shown to have the small model property and therefore decidable. (shrink)

ArgumentIn this essay, I sketch a problem-based framework within which I locate the concept of “organism” in the system theories of Georg Ernst Stahl, Théophile Bordeu, and Paul-Joseph Barthez. Around 1700, Stahl coins the word “organism” for a certain concept of order. For him, the concept explains the form of order of living bodies that is categorically different from the order of other bodies or composites. At the end of the century, the “organism” as a specific form of order becomes (...) a major topos in many discourses. I will not so much focus on experiments and objects as on basic problems that contribute to the general framework of the concept of organism as a key concept of the vitalist movement between 1700 and 1800. For this purpose, I will investigate the combination of three explanatory tools. These tools refer to regulating agents, functional interactions, and stimulus-reactions-schemes within individual organic systems of forces. They are related to various themes – especially to energy, sensibility, and sympathy. I will retrace some aspects of these relations. (shrink)

Cognitive modeling of human behavior has advanced the understanding of underlying processes in several domains of psychology and cognitive science. In this article, we outline how we expect cognitive modeling to improve comprehension of individual cognitive processes in human-agent interaction and, particularly, human-robot interaction (HRI). We argue that cognitive models offer advantages compared to data-analytical models, specifically for research questions with expressed interest in theories of cognitive functions. However, the implementation of cognitive models is arguably more complex than common statistical (...) procedures. Additionally, cognitive modeling paradigms typically have an explicit commitment to an underlying computational theory. We propose a conceptual framework for designing cognitive models that aims to identify whether the use of cognitive modeling is applicable to a given research question. The framework consists of five external and internal aspects related to the modeling process: research question, level of analysis, modeling paradigms, computational properties, and iterative model development. In addition to deriving our framework from a concise literature analysis, we discuss challenges and potentials of cognitive modeling. We expect cognitive models to leverage personalized human behavior prediction, agent behavior generation, and interaction pretraining as well as adaptation, which we outline with application examples from personalized HRI. (shrink)

The idea of representation is central to many theories for embodied skillful action. Representation-centric cognition has been questioned in light of the prominence of E-cognition in the past two decades, including ecological psychology, sensorimotor theory, dynamical systems, and 4E cognition. The paper expands on the critique by offering alternate explanations for the information processing model of skill learning and embodied action. Mental representation plays a fundamental role in information processing explanations of embodied skillful action. The skilled activity is considered discretely (...) in information-theoretic approaches, consisting of a linear model of information input-process-output. According to the paper, the beginning, emergence, acquisition, performance, and mastery of an embodied skilled activity are all part of a human experience continuum. Using vehicle driving as an example, the paper examines diverse viewpoints on embodied skillful action. (shrink)

Gaze following occurs automatically in social interactions, but the degree to which gaze is followed depends on whether an agent is perceived to have a mind, making its behavior socially more relevant for the interaction. Mind perception also modulates the attitudes we have towards others, and deter-mines the degree of empathy, prosociality and morality invested in social interactions. Seeing mind in others is not exclusive to human agents, but mind can also be ascribed to nonhuman agents like robots, (...) as long as their appearance and/or behavior allows them to be perceived as intentional beings. Previous studies have shown that human appearance and reliable behavior induce mind perception to robot agents, and positively affect attitudes and performance in human-robot interaction. What has not been investigated so far is whether different triggers of mind perception have an independent or interactive effect on attitudes and performance in human-robot interaction. We examine this question by manipulating agent appearance (human vs. robot) and behavior (reliable vs. random) within the same paradigm and examine how congruent (human/reliable vs. robot/random) versus incongruent (human/random vs. robot/reliable) combinations of these triggers affect performance (i.e., gaze fol-lowing) and attitudes (i.e., agent ratings) in human-robot interaction. The results show that both ap-pearance and behavior affect human-robot interaction but that the two triggers seem to operate in iso-lation, with appearance more strongly impacting attitudes, and behavior more strongly affecting per-formance. The implications of these findings for human-robot interaction are discussed. (shrink)

In this article, we suggest that the study of social interactions and the development of a “sense of agency” in joint action can help determine the content of relevant explanations to be implemented in artificial systems to make them “explainable.” The introduction of automated systems, and more broadly of Artificial Intelligence, into many domains has profoundly changed the nature of human activity, as well as the subjective experience that agents have of their own actions and their consequences – an (...) experience that is commonly referred to as sense of agency. We propose to examine the empirical evidence supporting this impact of automation on individuals’ sense of agency, and hence on measures as diverse as operator performance, system explicability and acceptability. Because of some of its key characteristics, AI occupies a special status in the artificial systems landscape. We suggest that this status prompts us to reconsider human–AI interactions in the light of human–human relations. We approach the study of joint actions in human social interactions to deduce what key features are necessary for the development of a reliable sense of agency in a social context and suggest that such framework can help define what constitutes a good explanation. Finally, we propose possible directions to improve human–AI interactions and, in particular, to restore the sense of agency of human operators, improve their confidence in the decisions made by artificial agents, and increase the acceptability of such agents. (shrink)

In this paper, we use some elements of the philosophical theories of Wilfrid Sellars and Robert Brandom for examining the interactions between humans and machines. In particular, we adopt the concept of the space of reasons for analyzing the status of artificial intelligent agents. One could argue that AIAs, like the widely used recommendation systems, have already entered the space of reasons, since they seem to make knowledge claims that we use as premises for further claims. This, in turn, (...) can lead to a sense of alienation because AIAs do not quite play by the rules of the space of the reason. We, therefore, ask somewhat pointedly whether aliens have entered the space of reasons. A closer look reveals that it is a misconception to consider AIAs as being in the space of reasons. In fact, they should be seen as very sophisticated tools. Since these tools affect our own acting in the space of reasons, special regulations are required for their proper use. (shrink)

Many logical systems today describe intelligent interacting agents over time. Frameworks include Interpreted Systems (IS, Fagin et al. [8]), Epistemic-Temporal Logic (ETL, Parikh & Ramanujam [22]), STIT (Belnap et al. [5]), Process Algebra and Game Semantics (Abramsky [1]). This variety is an asset, as different modeling tools can be fine-tuned to specific applications. But it may also be an obstacle, when barriers between paradigms and schools go up. This paper takes a closer look at one particular interface, between (...) two systems that both address the dynamics of knowledge and information flow in multi-agent systems. One is IS/ETL (IS and ETL are, from a technical point of view, the same up to model transformations, cf. [20]), which uses linear or branching time models with added epistemic structure induced by agents’ different capabilities for observing events. These models provide a Grand Stage where histories of some process unfold constrained by a protocol, and a matching epistemic-temporal language describes what happens. The other framework is Dynamic Epistemic Logic (DEL, [10, 4, 34]) that describes interactive processes in terms of epistemic event models which may occur inside modalities of the language. Temporal evolution is then computed from some initial epistemic model through a process of successive ‘product updates’. It has long been unclear how to best compare IS/ETL and DEL. Various aspects have been investigated in [10, 30, 32], but in this paper, we study the interface in a more systematic way. Often, DEL and ETL are presented as alternative ways of adding dynamics to multi-agent epistemic models. In this paper, we rather focus on how merging the two different modeling choices leads to interesting new questions. Our leading interest here will be a view of informational processes as evolving over time. To see what we mean, consider the simplest version of DEL, viz. the logic of public announcements PAL ([23]) which adds a very specific type of communicative 1 action to epistemic models: a public announcement.. (shrink)

In this position paper for the 2019 CSCW workshop Good Systems: Ethical AI for CSCW I propose one tool and one idea for navigating the complex ethical problem space that results from the interaction of human and/or AI agents in shared, hopefully cooperative, computing environments.

Clark and Fischer argue that people see social robots as depictions of social agents. However, people's interactions with virtual assistants may change their beliefs about social robots. Children and adults with exposure to virtual assistants may view social robots not as depictions of social agents, but as social agents belonging to a unique ontological category.

To explain agent-identification behaviours, universalist theories in the biological and cognitive sciences have posited mental mechanisms thought to be universal to all humans, such as agent detection and face recognition mechanisms. These universalist theories have paid little attention to how particular sociocultural or historical contexts interact with the psychobiological processes of agent-identification. In contrast to universalist theories, contextualist theories appeal to particular historical and sociocultural contexts for explaining agent-identification. Contextualist theories tend to adopt idiographic methods aimed at recording the heterogeneity (...) of human behaviours across history, space, and cultures. Defenders of the universalist approach tend to criticise idiographic methods because such methods can lead to relativism or may lack generality. To overcome explanatory limitations of proposals that adopt either universalist or contextualist approaches in isolation, I propose a philosophical model that integrates contributions from both traditions: the psycho-historical theory of agent-identification. This theory investigates how the tracking processes that humans use for identifying agents interact with the unique socio-historical contexts that support agent-identification practices. In integrating hypotheses about the history of agents with psychological and epistemological principles regarding agent-identification, the theory can generate novel hypotheses regarding the distinction between recognition-based, heuristic-based, and explanation-based agent-identification. (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)

The construction of embodied conversational agents - robots as well as avatars - seem to be a new challenge in the field of both cognitive AI and human-computer-interface development. On the one hand, one aims at gaining new insights in the development of cognition and communication by constructing intelligent, physical instantiated artefacts. On the other hand people are driven by the idea, that humanlike mechanical dialog-partners will have a positive effect on human-machine-communication. In this contribution I put for discussion (...) whether the visions of scientist in this field are plausible and which problems might arise by the realization of such projects. (shrink)

A semantics is presented for belief-revision in the face of common announcements to a group of agents that have beliefs about each other's beliefs. The semantics is based on the idea that possible worlds can be viewed as having an internal structure, representing the belief independent features of the world, and the respective belief states of the agents in a modular fashion. Modularity guarantees that changing one aspect of the world (a belief independent feature or a belief state) (...) has no effect on any other aspect of the world. This allows us to employ an AGM-style selection function to represent revision. The semantics is given a complete axiomatisation (identical to the axiomatisation found by Gerbrandy and Groeneveld for a semantics based on non-wellfounded set theory) for the special case of expansion. (shrink)

The study of human-human communication and the development of computational models for human-agent communication have diverged significantly throughout the last decade. Yet, despite frequently made claims of “super-human performance” in, e.g., speech recognition or image processing, so far, no system is able to lead a half-decent coherent conversation with a human. In this paper, we argue that we must start to re-consider the hallmarks of cooperative communication and the core capabilities that we have developed for it, and which conversational (...) class='Hi'>agents need to be equipped with: incremental joint co-construction and mentalizing. We base our argument on a vast body of work on human-human communication and its psychological processes that we reason to be relevant and necessary to take into account when modeling human-agent communication. We contrast those with current conceptualizations of human-agent interaction and formulate suggestions for the development of future systems. (shrink)

Temporal epistemic logics are known, from results of Halpern and Vardi, to have a wide range of complexities of the satisfiability problem: from PSPACE, through non-elementary, to highly undecidable. These complexities depend on the choice of some key parameters specifying, inter alia, possible interactions between time and knowledge, such as synchrony and agents' abilities for learning and recall. In this work we develop practically implementable tableau-based decision procedures for deciding satisfiability in single-agent synchronous temporal-epistemic logics with interactions between time (...) and knowledge. We discuss some complications that occur, even in the single-agent case, when interactions between time and knowledge are assumed and show how the method of incremental tableaux can be adapted to work in EXPSPACE, respectively 2EXPTIME, for these logics, thereby also matching the upper bounds obtained for them by Halpern and Vardi. (shrink)

A semantics is presented for belief revision in the face of common announcements to a group of agents that have beliefs about each other’s beliefs. The semantics is based on the idea that possible worlds can be viewed as having an internal-structure, representing the belief independent features of the world, and the respective belief states of the agents in a modular fashion. Modularity guarantees that changing one aspect of the world (a belief independent feature or a belief state) (...) has no effect on any other aspect of the world. This allows us to employ an AGM-style selection function to represent revision. The semantics is given a complete axiomatisation (identical to the axiomatisation found by Gerbrandy and Groeneveld for a semantics based on non-wellfounded set theory) for the special case of expansion. (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)

Contemporary epistemological and cognitive studies, as well as recent trends in computer science and game theory have revealed an increasingly important and intimate relationship between Information, Interaction, and Agency. Agents perform actions based on the available information and in the presence of other interacting agents. From this perspective Information, Interaction, and Agency neatly ties together classical themes like rationality, decision-making and belief revision with games, strategies and learning in a multi-agent setting. Unified by the central notions Information, (...) Interaction, and Agency, the essays in this volume provide refreshing methodological perspectives on belief revision, dynamic epistemic logic, von Neumann games, and evolutionary game theory; all of which in turn are central approaches to understanding our own rationality and that of other agents. (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.