This article provides an answer to the question: What is the function of cognition? By answering this question it becomes possible to investigate what are the simplest cognitive systems. It addresses the question by treating cognition as a solution to a design problem. It defines a nested sequence of design problems: (1) How can a system persist? (2) How can a system affect its environment to improve its persistence? (3) How can a system utilize better information from the environment (...) to select better actions? And, (4) How can a system reduce its inherent informational limitations to achieve more successful behavior? This provides a corresponding nested sequence of system classes: (1) autonomous systems, (2) (re)active autonomous systems, (3) informationally controlled autonomous systems (autonomous agents), and (4) cognitive systems. -/- This article provides the following characterization of cognition: The cognitive system is the set of mechanisms of an autonomous agent that (1) allow increase of the correlation and integration between the environment and the information system of the agent, so that (2) the agent can improve the selection of actions and thereby produce more successful behavior. -/- Finally, it shows that common cognitive capacities satisfy the characterization: learning, memory, representation, decision making, reasoning, attention, and communication. (shrink)

Some intriguing questions such as: What is reality for an agent? How does reality of a bacterium differ from a reality of a human brain? Do we need representation in order to understand reality? are still widely debated. Starting with the presentation of the computing nature as an info-computational framework, where information is defined as a structure, and computation as information processing, we address questions of evolution of increasingly complex living agents through interactions with the environment. In this context, (...) the concept of computation will be discussed and the sense in which computation is observer-relative. Using the results on morphological/ morphogenetic computation as information self-organization we argue that reality for an agent is a result of networked agent-based computation. Consciousness is a (computational) process of information integration that evolved in organisms with nervous system. We present an argument why pancomputationalism (computing nature) is a sound scientific strategy and why panpsychism is not. (shrink)

Cognition, writ broadly to include motivation and emotion, is best conceived of as control structure for autonomous agents . Autonomous agents are situated in a environment. They both sense and act on that environment, over time, so as to effect subsequent sensing. Examples of such agents include humans, animals, some mobile robots, some artificial life creatures (who "live" in a simulated environment on a computer) and some software agents (who "live" in a file system, a database, or on a network). (...) Their actions are in pursuit of their own agendas, as designed in by their maker or programmer, or as evolved and shaped by culture. Each such agent employs some control mechanism whose continual duty is to select the next action. The term "cognition," in its broad sense, refers to the workings of such control mechanisms. (shrink)

Commonsense reasoning is a crucial human ability employed in everyday tasks. In this talk I provide a knowledge level analysis of the main representational and reasoning problems affecting the cognitive architectures for what concerns this issue. In providing this analysis I will show, by considering some of the main cognitive architectures currently available (e.g. SOAR, ACT-R, CLARION), how one of the main problems of such architectures is represented by the fact that their knowledge representation and processing mechanisms are (...) not sufficiently constrained with insights coming from cognitive science (Lieto 2021; Lieto, Lebiere, Oltramari, 2018). As a possible way out to such knowledge processing issues, I present the main assumptions that have led to the development of the Dual PECCS categorization system (Lieto, Radicioni, Rho 2017) and discuss some of the lessons learned and their possible implications in the design of the knowledge modules and knowledge-processing mechanisms of integrated cognitive architectures. (shrink)

What is reality for an agent? What is minimal cognition? How does the morphology of a cognitive agent affect cognition? These are still open questions among scientists and philosophers. In this chapter we propose the idea of info-computational nature as a framework for answering those questions. Within the info-computational framework, information is defined as a structure, and computation as the dynamics of information. To an agent, nature therefore appears as an informational structure with computational dynamics. Both (...) information and computation in this context have broader meaning than in everyday use, and both are necessarily grounded in physical implementation. Evolution of increasingly complex living agents is understood as a process of morphological computation driven by agents’ interactions with the environment. It is a process much more complex than random variation; instead the mechanisms of change are morphological computational processes of self-organisation. Reality for an agent emerges as a result of interactions with the environment together with internal information processing. Following Maturana and Varela, we take cognition to be the process of living of an organism, and thus it appears on different levels of complexity, from cellular via organismic to social. The simpler the agent, the simpler its “reality” defined by the network of networks of info-computational processes, which constitute its cognition. The debated topic of consciousness takes its natural place in this framework, as a process of information integration that we suggest naturally evolved in organisms with a nervous system. Computing nature/pancomputationalism is sometimes confused with panpsychism or claimed to necessarily imply panpsychism, which we show is not the case. Even though we focus on natural systems in this chapter, the info-computational approach is general and can be used to model both biological and artifactual cognitive agents. (shrink)

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we separately analyze the operation of this agent using the mathematical tools of information theory and dynamical systems theory. Information-theoretic analysis reveals how task-relevant information flows through the system to be (...) combined into a categorization decision. Dynamical analysis reveals the key geometrical and temporal interrelationships underlying the categorization decision. Finally, we propose a framework for directly relating these two different styles of explanation and discuss the possible implications of our analysis for some of the ongoing debates in cognitive science. (shrink)

This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the natural/morphological computational (...) models and their relationships to physical systems, especially cognitive systems such as living beings. Natural morphological infocomputation as a conceptual framework necessitates generalization of models of computation beyond the traditional Turing machine model presenting symbol manipulation, and requires agent-based concurrent resource-sensitive models of computation in order to be able to cover the whole range of phenomena from physics to cognition. The central role of agency, particularly material vs. cognitive agency is highlighted. (shrink)

The article describes the author's approach to the construction of general-level artificial cognitive agents based on the so-called "semantic supervised learning", within which, in accordance with the hybrid paradigm of artificial intelligence, both machine learning methods and methods of the symbolic ap­ proach and knowledge-based systems are used ("good old-fashioned artificial intelligence"). А descrip­ tion of current proЬlems with understanding of the general meaning and context of situations in which narrow AI agents are found is presented. The definition of (...) semantic supervised learning is given and its relationship with other machine learning methods is described. In addition, а thought experiment is presented, which shows the essence and meaning of supervised semantic learning. (shrink)

Natural languages vary in their quantity expressions, but the variation seems to be constrained by general properties, so-calleduniversals. Their explanations have been sought among constraints of human cognition, communication, complexity, and pragmatics. In this article, we apply a state-of-the-art language coordination model to the semantic domain of quantities to examine whether two quantity universals—monotonicity and convexity—arise as a result of coordination. Assuming precise number perception by the agents, we evolve communicatively usable quantity terminologies in two separate conditions: a numeric-based condition (...) in which agents communicate about a number of objects and a quotient-based condition in which agents communicate about the proportions. We find out that both universals take off in all conditions but only convexity almost entirely dominates the emergent languages. Additionally, we examine whether the perceptual constraints of the agents can contribute to the further development of universals. We compare the degrees of convexity and monotonicity of languages evolving in populations of agents with precise and approximate number sense. The results suggest that approximate number sense significantly reinforces monotonicity and leads to further enhancement of convexity. Last but not least, we show that the properties of the evolved quantifiers match certain invariance properties from generalized quantifier theory. (shrink)

Cognitive science is unusual in that cognitive scientists have dramatic disagreements about the extension of their object of study, cognition. This paper defends a novel analysis of the scientific concept of cognition: that cognition is the sensitive management of an agent’s behavior. This analysis is “modular,” so that its extension varies depending on how one interprets certain of its constituent terms. I argue that these variations correspond to extant disagreements between cognitive scientists. This correspondence is evidence (...) that the proposed analysis models the contemporary understanding of cognition among scientists, without artificially resolving questions that are currently considered open. (shrink)

Propositional attitudes, such as beliefs, desires, and intentions, can be attributed to collective agents. In my paper I focus on cognitive attitudes, and I explore the various types of collective beliefs. I argue that there is a whole spectrum of collective beliefs, and I distinguish between two extremes: the weak opinion poll conception and the strong agreement-based conception. Strong collective beliefs should be understood in terms of the acceptance of a proposition rather than of belief proper. They are not (...) purely epistemic and involve practical considerations. To believe that p collectively in the strong sense is to adopt a policy to use that proposition in the group’s deliberations about future actions. (shrink)

Agentive awareness is one's awareness of oneself as presently acting. Dominant accounts in cognitive science consider agentive awareness to be grounded in the states and processes underlying sensorimotor control. In this paper, I raise concerns for this approach and develop an alternative. Broadly, in the approach I defend, one is agentively aware in the virtue of intending to act. I further argue that agentive awareness is not constituted by intentions themselves but rather first-personal thoughts that are formed on the (...) basis of them. I develop this proposal, highlight some of its theoretical advantages, and show how it successfully meets various challenges. (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 paper introduces a novel perspective on Agentive Cognitive Construction Grammar (AgCCxG) by examining the intricate interplay between mind and language through the lens of both Active Inference and Peircean semiotics. AgCCxG emphasizes the impact of intention and purpose on linguistic choices as a cognitive imperative to balance the symbolic Self (Intelligent Agent) with the dynamics of the environment. Among other things, the paper posits that linguistic constructions, particularly Constructional Attachment Patterns (CAPs), like argument structure constructions, embody (...) experienced interactions with the world through reenactment routines via the integration of multisensory channels. Unlike traditional usage-based approaches (e.g., construction grammars), AgCCxG embraces a robust theory of signs that reveals human representation as a continuous process of semiotic hybridization for the creative prediction of uncertain scenarios. Importantly, the paper challenges the notion of the mind as a unified, rational, uncertainty-reducing machine by asserting that physical processes governing open biological systems profoundly influence the linguistic sign system. Intelligent agents’ adaptability in expressing incongruous realities thus highlights the role of semiotic hybridization in preserving an agent’s autonomy and semiotic boundary. (shrink)

In this paper the cognitive, cultural, and linguistic bases for a pattern of conventionalization of two types of iconic handshapes are described. Work on sign languages has shown that handling handshapes and object handshapes express an agentive/non-agentive semantic distinction in many sign languages. H-HSs are used in agentive event descriptions and O-HSs are used in non-agentive event descriptions. In this work, American Sign Language and Italian Sign Language productions are compared as well as the corresponding groups of gesturers in (...) each country using “silent gesture.” While the gesture groups, in general, did not employ an H-HS/O-HS distinction, all participants used iconic handshapes more often in agentive than in no-agent event descriptions; moreover, none of the subjects produced an opposite pattern than the expected one . These effects are argued to be grounded in cognition. In addition, some individual gesturers were observed to produce the H-HS/O-HS opposition for agentive and non-agentive event descriptions—that is, more Italian than American adult gesturers. This effect is argued to be grounded in culture. Finally, the agentive/non-agentive handshape opposition is confirmed for signers of ASL and LIS, but previously unreported cross-linguistic differences were also found across both adult and child sign groups. It is, therefore, concluded that cognitive, cultural, and linguistic factors contribute to the conventionalization of this distinction of handshape type. (shrink)

Standard notions in philosophy of mind have a tendency to characterize socio-cognitive abilities as if they were unique to sophisticated human beings. However, assuming that it is likely that we are soon going to share a large part of our social lives with various kinds of artificial agents, it is important to develop a conceptual framework providing notions that are able to account for various types of social agents. Recent minimal approaches to socio-cognitive abilities such as mindreading and (...) commitment present a promising starting point from which one can expand the field of application not only to infants and non-human animals but also to artificial agents. Developing a minimal approach to the socio-cognitive ability of acting jointly, I present a foundation for future discussions about the question of how our conception of sociality can be expanded to artificial agents. (shrink)

In the current research on multi-agent systems (MAS), many theoretical issues related to sociocultural processes have been touched upon. These issues are in fact intellectually profound and should prove to be significant for MAS. Moreover, these issues should have equally significant impact on cognitive science, if we ever try to understand cognition in the broad context of sociocultural environments in which cognitive agents exist. Furthermore, cognitive models as studied in cognitive science can help us in (...) a substantial way to better probe multi-agent issues, by taking into account essential characteristics of cognitive agents and their various capacities. In this paper, we systematically examine the interplay among social sciences, MAS, and cognitive science. We try to justify an integrated approach for MAS which incorporates different perspectives. We show how a new cognitive model, CLARION, can embody such an integrated approach through a combination of autonomous learning and assimilation. (shrink)

Purpose:To test the hypothesis that supernatural agents appear in nightmares and dreams in association with evidence of diminished agency within the dreamer/dream ego.Methods:Content analyses of 120 nightmares and 71 unpleasant control dream narratives.Results:We found that SAs overtly occur in about one quarter of unpleasant dreams and about half of nightmares. When SAs appear in a dream or nightmare they are reliably associated with diminished agency in the dreamer. Diminished agency within the dreamer occurs in over 90% of dreams that have (...) overt SAs. In about half of nightmare reports the SA appears suddenly with no clear emergence pattern. In some two thirds of unpleasant dreams, however, the SA emerged from a human character. The SA’s gender was indeterminate in most dreams with SAs but the SA communicated with the dreamer in 24% of nightmares and only 13% of unpleasant dreams. In most nightmares, the SA intended to harm the dreamer and in one third of nightmares the dreamer was the victim of physical agression by the SA. SA intentions in unpleasant dreams were more varied and actually benign in 13% of cases.Conclusion:Supernatural agents reliably appear in nightmares and unpleasant dreams in association with diminished agency in the dreamer. Diminished agency in an individual may facilitate supernatural agent cognitions. (shrink)

What is the function of cognition? On one influential account, cognition evolved to co-ordinate behaviour with environmental change or complexity. Liberal interpretations of this view ascribe cognition to an extraordinarily broad set of biological systems—even bacteria, which modulate their activity in response to salient external cues, would seem to qualify as cognitive agents. However, equating cognition with adaptive flexibility per se glosses over important distinctions in the way biological organisms deal with environmental complexity. Drawing on contemporary advances in theoretical (...) biology and computational neuroscience, we cash these distinctions out in terms of different kinds of generative models, and the representational and uncertainty-resolving capacities they afford. This analysis leads us to propose a formal criterion for delineating cognition from other, more pervasive forms of adaptive plasticity. On this view, biological cognition is rooted in a particular kind of functional organisation; namely, that which enables the agent to detach from the present and engage in counterfactual inference. (shrink)

In this article, I argue for cooperation as a three-dimensional phenomenon lying on the continua of a cognitive, a behavioural, and an affective axis. Traditional accounts of joint action argue for cooperation as involving a shared intention. Developmental research has shown that such cooperation requires rather sophisticated social cognitive skills such as having a robust theory of mind - that is acquired not until age 4 to 5 in human ontogeny. However, also younger children are able to cooperate (...) in various ways. Moreover, the coordinated behaviours of the agents can be more or less complex. Finally, phenomenological considerations and findings from social psychology illustrate that affective states and agent-specificities may play a central role in cooperative activities. I end with discussing the implications of my analysis that speak in favour of a pluralist account of social cognition. (shrink)

Standard notions in philosophy of mind have a tendency to characterize socio-cognitive abilities as if they were unique to sophisticated human beings. However, assuming that it is likely that we are soon going to share a large part of our social lives with various kinds of artificial agents, it is important to develop a conceptual framework providing notions that are able to account for various types of social agents. Recent minimal approaches to socio-cognitive abilities such as mindreading and (...) commitment present a promising starting point from which one can expand the field of application not only to infants and non-human animals but also to artificial agents. Developing a minimal approach to the sociocognitive ability of acting jointly, I present a foundation for future discussions about the question of how our conception of sociality can be expanded to artificial agents. (shrink)

Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to (...) adaptive success. This target article critically examines this approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency. (shrink)

Rational decision making depends on what one believes, what one desires, and what one knows. In conventional decision models, beliefs are represented by probabilities and desires are represented by utilities. Software agents are knowledgeable entities capable of managing their own set of beliefs and desires, and they can decide upon the next operation to execute autonomously. They are also interactive entities capable of filtering communications and managing dialogues. Knowledgeability includes representing knowledge about the external world, reasoning with it, and sharing (...) it. Interactions include negotiations to perform tasks in cooperative, coordinative, and competitive ways. In this paper we focus on decision-making mechanisms for agent-based systems on the basis of agent interaction. We identify possible interaction scenarios and define mechanisms for decision making in uncertain environments. It is believed that software agents will become the underlying technology that offers the capability of distribution of competence, control, and information for the next generation of ubiquitous, distributed, and heterogeneous information systems. (shrink)

As we know, a cognitive architecture is a domain-generic computational cognitive model that may be used for a broad analysis of cognition and behavior. Cognitive architectures embody theories of cognition in computer algorithms and programs. Social simulation with multi-agent systems can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents (as argued in Sun 2001). In this survey, an example cognitive architecture will be given, and its application to (...) social simulation will be sketched. (shrink)

I shall argue that software agents can be attributed cognitive states, since their behaviour can be best understood by adopting the intentional stance. These cognitive states are legally relevant when agents are delegated by their users to engage, without users’ review, in choices based on their the agents’ own knowledge. Consequently, both with regard to torts and to contracts, legal rules designed for humans can also be applied to software agents, even though the latter do not have rights (...) and duties of their own. The implications of this approach in different areas of the law are then discussed, in particular with regard to contracts, torts, and personality. (shrink)

This article argues for a task-based approach to identifying and individuating cognitive systems. The agent-based extended cognition approach faces a problem of cognitive bloat and has difficulty accommodating both sub-individual cognitive systems ("scaling down") and some supra-individual cognitive systems ("scaling up"). The standard distributed cognition approach can accommodate a wider variety of supra-individual systems but likewise has difficulties with sub-individual systems and faces the problem of cognitive bloat. We develop a task-based variant of distributed (...) cognition designed to scale up and down smoothly while providing a principled means of avoiding cognitive bloat. The advantages of the task-based approach are illustrated by means of two parallel case studies: re-representation in the human visual system and in a biomedical engineering laboratory. (shrink)

This article compares the ability to track individuals lacking mental states with the ability to track intentional agents. It explains why reference to individuals raises the problem of explaining how cognitive agents track unique individuals and in what sense reference is based on procedures of perceptual-motor and epistemic tracking. We suggest applying the notion of singular-files from theories in perception and semantics to the problem of tracking intentional agents. In order to elucidate the nature of agent-files, three views (...) of the relation between object- and agent-tracking are distinguished: the Independence, Deflationary and Organism-Dependence Views. The correct view is argued to be the latter, which states that perceptual and epistemic tracking of a unique human organism requires tracking both its spatio-temporal object-properties and its agent-properties. (shrink)

Rational decision making depends on what one believes, what one desires, and what one knows. In conventional decision models, beliefs are represented by probabilities and desires are represented by utilities. Software agents are knowledgeable entities capable of managing their own set of beliefs and desires, and they can decide upon the next operation to execute autonomously. They are also interactive entities capable of filtering communications and managing dialogues. Knowledgeability includes representing knowledge about the external world, reasoning with it, and sharing (...) it. Interactions include negotiations to perform tasks in cooperative, coordinative, and competitive ways. In this paper we focus on decision-making mechanisms for agent-based systems on the basis of agent interaction. We identify possible interaction scenarios and define mechanisms for decision making in uncertain environments. It is believed that software agents will become the underlying technology that offers the capability of distribution of competence, control, and information for the next generation of ubiquitous, distributed, and heterogeneous information systems. (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)

Understanding the role of ‘‘representations’’ in cognitive science is a fundamental problem facing the emerging framework of embodied, situated, dynamical cognition. To make progress, I follow the approach proposed by an influential representational skeptic, Randall Beer: building artificial agents capable of minimally cognitive behaviors and assessing whether their internal states can be considered to involve representations. Hence, I operationalize the concept of representing as ‘‘standing in,’’ and I look for representations in embodied agents involved in simple categorization tasks. (...) In a first experiment, no representation can be found, but the relevance of the task is undermined by the fact that agents with no internal states can reach high performance. A simple modification makes the task more “representationally hungry,” and in this case, agents’ internal states are found to qualify as representations. I conclude by discussing the benefits of reconciling the embodied-dynamical approach with the notion of representation. (shrink)

Although there have been efforts to integrate Semantic Web technologies and artificial agents related AI research approaches, they remain relatively isolated from each other. Herein, we introduce a new ontology framework designed to support the knowledge representation of artificial agents’ actions within the context of the actions of other autonomous agents and inspired by standard cognitive architectures. The framework consists of four parts: 1) an event ontology for information pertaining to actions and events; 2) an epistemic ontology containing facts (...) about knowledge, beliefs, perceptions and communication; 3) an ontology concerning future intentions, desires, and aversions; and, finally, 4) a deontic ontology for modeling obligations and prohibitions which limit agents’ actions. The architecture of the ontology framework is inspired by deontic cognitive event calculus as well as epistemic and deontic logic. We also describe a case study in which the proposed DCEO ontology supports autonomous vehicle navigation. (shrink)

Distributed cognition refers to processes which are (i) cognitive and (ii) distributed across multiple agents or devices rather than performed by a single agent. Distributed cognition has attracted interest in several fields ranging from sociology and law to computer science and the philosophy of science. In this paper, I discuss distributed cognition from a social-choice-theoretic perspective. Drawing on models of judgment aggregation, I address two questions. First, how can we model a group of individuals as a distributed (...) class='Hi'>cognitive system? Second, can a group acting as a distributed cognitive system be ‘rational’ and ‘track the truth’ in the outputs it produces? I argue that a group’s performance as a distributed cognitive system depends on its ‘aggregation procedure’ – its mechanism for aggregating the group members’ inputs into collective outputs – and I investigate the properties of an aggregation procedure that matter. (shrink)

This article introduces Agentive Cognitive Construction Grammar, an emerging field that seeks to connect the linguistic system with speaker-meaning. The stated purpose is thus to tackle a pervasive disconnect in both cognitive linguistics and construction grammar, whereby the linguistic system and speaker selections are separated in the belief that language is essentially a mental process associated with the brain, and hence, separated from bodily experience. I contend this view by introducing a triadic model of construction in which form (...) and function are inextricably bound up with agency. This is possible because language is tethered to senses of movement and balance that connect experiences with the physical world with the mental. A major insight of the paper is that argument structure constructions partake of both linguistic and non-linguistic signs, which provides speakers with a means to verbalize their thoughts and distribute agency in specific events. (shrink)