As we move towards a world that is using machine learning and nascent artificial intelligence to analyse and, in many ways, guide most aspects of our lives, new forms of heterogeneous collaborative teams that include human/intelligent machine agents will become not just possible, but an inevitable part of our shared world. The conscious participation of the arts in the conversation about, and development and implementation of, these new collaborative possibilities is crucial, as the arts serve as our best (...) lens through which we can explore the full spectrum of potential possibilities and futures. Through the complex relationships formed through heterogeneous human/intelligent agent collaboration, we are given the opportunity to re-examine some of our assumptions and suppositions of teamwork and forms of relating and thinking within a group environment. (shrink)

This paper presents two formation tracking control strategies for a combined set of single and double integrator agents with an arbitrary undirected communication topology. The first approach is based on the design of distance-based potential functions with interagent collision avoidance using local information about the distance and orientation between agents and the desired trajectory. The second approach adds signed area constraints to the desired formation specification and a control strategy that uses distance as well as area terms is (...) designed to achieve tracking convergence. Numerical simulations show the performance from both control laws. (shrink)

The paper introduces an extension of the proposal according to which conceptual representations in cognitive agents should be intended as heterogeneous proxytypes. The main contribution of this paper is in that it details how to reconcile, under a heterogeneous representational perspective, different theories of typicality about conceptual representation and reasoning. In particular, it provides a novel theoretical hypothesis - as well as a novel categorization algorithm called DELTA - showing how to integrate the representational and reasoning assumptions (...) of the theory-theory of concepts with the those ascribed to the prototype and exemplars-based theories. (shrink)

The paper presents the heterogeneous proxytypes hypothesis as a cognitively-inspired computational framework able to reconcile, in both natural and artificial systems, different theories of typicality about conceptual representation and reasoning that have been traditionally seen as incompatible. In particular, through the Dual PECCS system and its evolution, it shows how prototypes, exemplars and theory-theory like conceptual representations can be integrated in a cognitive artificial agent (thus extending its categorization capabilities) and, in addition, can provide useful insights in the context (...) of a computationally grounded science of the mind. (shrink)

This chapter develops the concept of heterogeneous political space as an alternative to the exclusively human political sphere which dominates Western political thinking about collective action and justice. The aim is to make evident that capacities for action are constituted in heterogeneous milieus and to argue that insofar as political thought does not register this it is inadequate to thinking justice and flourishing in a world where ecological change renders human and nonhuman modes of life increasingly precarious. (...) class='Hi'>Heterogeneous political spaces are constituted by compositions of material, affect and desire which are occluded by humanist and individualist theories of action that theorise collective action at the register of a macro-political order made up of unified rational subjects with clear intentions and commitments. Gilles Deleuze and Félix Guattari’s concepts of following and assembling enable accounts of a molecular or micro-political register composed of het- erogeneous collectivities in processes of composition. In their insistence that human action cannot be separated from the productions of nature, we find that heterogeneity, rather than human plurality, is given as a condition of action. Conceiving of political action in terms of heterogeneity brings into view the processes by which capacities for political action are constituted by non- human forces, entities and elements. It focuses attention on that in virtue of which political action occurs, rather than on the intentional aspect of actions which aim to achieve an individualised interest (whether it be the interests of a human individual or individuated group). Heterogeneous political space complexifies our thinking about political action and diffuses the agency of political subjects so as to render our thinking more adequate in several sig- nificant regards. It provides a conceptual resource that brings the diverse human-nonhuman entanglements to the fore and thus acknowledges the differing ways that capacities for political action are constituted in different assemblages that always cmprise nonhumans. This disrupts the liberal, humanist view of politics where nonhumans are excluded from the domain of action and appear only as passive resources to be exploited for human plans and actions. Further, by challenging the view of the more-than-human world as passively ‘standing-reserve’ for the purposes of human agents, the concept of heterogeneous political space invites a critical questioning whether the conception of political space as exclusively human is capable of attending to issues of ecological justice where the well-being of humans and ecosystems is inextricable. In short, when the more-than-human world is excluded from conceptions of political space neither the needs of nonhumans (plants, animals, ecosystems, waterways) nor the constitution of human cap- acities in relation with nonhumans (co-habitation, dependence, care) register as politically significant. This, in effect, obscures the ways that different human-nonhuman assemblages increase and diminish capacities for action. (shrink)

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)

The agent-relative/agent-neutral distinction is very well established and widely employed in the metaethical literature. However, I argue that there are actually two different senses of the distinction at large: the hetero-/homogeneous sense and the dependence/independence sense. The traditional, unqualified distinction ought, therefore, to be amended, with each use of the distinction being stipulated as used in either the hetero-/homogeneous sense or the dependence/independence sense. Careful analysis of various metaethics supports that there are these two senses – analysis, in particular, of (...) a neo-Kantian metaethic, according to which reasons are agent-relative in the dependence sense but agent-neutral in the homogeneous sense, and – perhaps surprisingly – of Utilitarianism, according to which reasons are agent-neutral in the independence sense but agent-relative in the heterogeneous sense. (shrink)

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 paper provides a novel axiomatic analysis of exploitation as the unequal exchange of labour in economies with heterogeneous optimising agents endowed with unequal amounts of physical and human capital. A definition of exploitation is proposed, which emphasises the relational nature of exploitation and the resulting inequalities in the allocation of labour and income. It is shown that, among all of the major definitions, this is the only one which satisfies two formally weak and normatively salient axioms, and (...) allows one to generalise a number of core insights of exploitation theory. (shrink)

This paper investigates the event-based consensus problem for the heterogeneous hybrid multiagent system. First, the heterogeneous hybrid MAS is proposed which contains continuous and discrete-time subsystems with second-order and first-order heterogeneous dynamics. Second, the event-triggered protocols are proposed, which mainly include the event-based control laws and event-triggered conditions for different kinds of agents. Then, the consensus conclusions of fixed topology and switching topologies are obtained based on graph theory and nonnegative matrix theory, which include the constraints (...) on control parameters, coupling gains, and sampling interval to guarantee consensus. Finally, a simulation example is given to verify the efficiency of the proposed protocols. (shrink)

I explore heterogeneous constructionism, my term for the perspective that science in the making is a process of agents building by combining a diversity of components. Issues addressed include causality and explanation; transcending both realism and relativism; scientists as acting, intervening, and imaginative agents; explanations that span many levels of social practice; counterfactuals in the analysis of causal claims; and practical reflexivity. An analogy from research on the social origins of depression and a sketch from my own (...) experience in socioeconomic modeling are used to motivate and render more concrete the form of heterogeneous constructionism I am advocating. (shrink)

This paper wishes to problematize the foundations of production governance and offer an analytical perspective on the interrelation between agents’ preferences, strategic choice, and the public sphere . The value is in the idea of preferences being social in nature and in the application both to the internal stakeholders of the organisation and its impacts on people outside. Using the concept of ‘strategic failure’ we suggest that social preferences reflected in deliberative social praxis can reduce false beliefs and increase (...) individual wellbeing. From this approach, the paper offers a taxonomy of production organisations, based on social preferences about two variables: the governance form other strategic decisions that characterize the management of a company at a more operational level, once its fundamental legal form has been chosen. Each dimension is then categorised alongside two basic preferences: towards inclusion or exclusion of ‘publics’ that have no substantial access to decision power about these variables. Our framework explains governance heterogeneity by contrasting exclusive and inclusive social preferences in cooperatives, social enterprises, as well as traditional corporations. A discussion of the evolution of social preferences and organizational forms is addressed through examples and regional experiences. (shrink)

Designing a data-responsive system requires accurate input to ensure efficient results. The growth of technology in sensing methods and the needs of various kinds of data greatly impact data fusion (DF)-related study. A coordinative DF framework entails the participation of many subsystems or modules to produce coordinative features. These features are utilized to facilitate and improve solving certain domain problems. Consequently, this paper proposes a general Multiple Coordinative Data Fusion Modules (MCDFM) framework for real-time and heterogeneous data sources. We (...) develop the MCDFM framework to adapt various DF application domains requiring macro and micro perspectives of the observed problems. This framework consists of preprocessing, filtering, and decision as key DF processing phases. These three phases integrate specific purpose algorithms or methods such as data cleaning and windowing methods for preprocessing, extended Kalman filter (EKF) for filtering, fuzzy logic for local decision, and software agents for coordinative decision. These methods perform tasks that assist in achieving local and coordinative decisions for each node in the network of the framework application domain. We illustrate and discuss the proposed framework in detail by taking a stretch of road intersections controlled by a traffic light controller (TLC) as a case study. The case study provides a clearer view of the way the proposed framework solves traffic congestion as a domain problem. We identify the traffic features that include the average vehicle count, average vehicle speed (km/h), average density (%), interval (s), and timestamp. The framework uses these features to identify three congestion periods, which are the nonpeak period with a congestion degree of 0.178 and a variance of 0.061, a medium peak period with a congestion degree of 0.588 and a variance of 0.0593, and a peak period with a congestion degree of 0.796 and a variance of 0.0296. The results of the TLC case study show that the framework provides various capabilities and flexibility features of both micro and macro views of the scenarios being observed and clearly presents viable solutions. (shrink)

This paper uses agent-based modelling to study the frequent booms and busts in Chinese agricultural markets. First, an artificial agricultural commodity market consisting of heterogeneous agents, such as producers, consumers, and speculators, is built. A numerical simulation suggests that speculation can cause large price fluctuations via nonlinear price dynamics. Then, parameters are estimated by the simulated method of moments using garlic and ginger price data in China from 2006Q2 to 2018Q3. The estimation yields a statistically significant speculative behavior (...) parameter, supporting speculators’ existence. Based on the well-estimated model, a low-cost policy experiment aiming at market stabilization is carried out. The essence of this policy is to release the theoretical steady state of the estimated model as the government-guided price to producers. The guided price, even partially followed by producers, can reduce simulated price variances and weaken speculators’ negative impact on market stability. Robustness tests show that the effect of policy experiment is robust under a 20% change in any parameter value or a 5% change in the guided price. (shrink)

An investigation into the conditions conducive to the emergence of heterogeneity amoung agents is presented. This is done by using a model of creative artificial agents to investigate some of the possibilities. The simulation is based on Brian Arthur's 'El Farol Bar' model but extended so that the agents also learn and communicate. The learning and communication is implemented using an evolutionary process acting upon a population of strategies inside each agent. This evolutionary learning process is based (...) on a Genetic Programming algorithm. This is chosen to make the agents as creative as possible and thus allow the outside edge of the simulation trajectory to be explored. A detailed case study from the simulations show how the agents have differentiated so that by the end of the run they had taken on qualitatively different roles. It provides some evidence that the introduction of a flexible learning process and an expressive internal representation has facilitated the emergence of this heterogeneity. (shrink)

This book argues that this powerful technique permits the social sciences to meet an explanation, in which one 'grows' the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors.

Gliomas are diffuse and invasive brain tumors with the nefarious ability to evade even seemingly draconian treatment measures. Here we introduce a simple mathematical model for drug delivery of chemotherapeutic agents to treat such a tumor. The model predicts that heterogeneity in drug delivery related to variability in vascular density throughout the brain results in an apparent tumor reduction based on imaging studies despite continual spread beyond the resolution of the imaging modality. We discuss a clinical example for which (...) the model-predicted scenario is relevant. The analysis and results suggest an explanation for the clinical problem of the long-standing confounding observation of shrinkage of the lesion in certain areas of the brain with continued growth in other areas. (shrink)

NEMO means Network Mobility which is the extension of Mipv6 and it is invented for accessing internet for the group of people when they are travelling in Vehicle as Network group. During handoff while exchanging Binding Updates between the Mobile Network Node, Correspondent Node and Home Agent, many security threats are present during those messages exchange. It may prone to several standard malicious attacks on the BU and Binding Acknowledgement. An efficient end-to-end security method is required to protect the BU (...) Exchange between MNN, HA and CN. In this paper, a secure architecture is proposed to provide authentication and confidentiality at each level of communication using a 3-Party Key Exchange called 3-PKE-NEMO with the help of Bilinear Pairing Theorem. Handoff delay is reduced without compromising security strength. The whole experimentation of this proposed work is carried out using NS2 simulation tool and authentication proof is given using BAN logic between all the nodes in NEMO. The proposed security architecture is compared with related existing solutions and found to be more secure. (shrink)

In the paper, several data reduction techniques for machine learning from big datasets are discussed and evaluated. The discussed approach focuses on combining several techniques including stacking, rotation, and data reduction aimed at improving the performance of the machine classification. Stacking is seen as the technique allowing to take advantage of the multiple classification models. The rotation-based techniques are used to increase the heterogeneity of the stacking ensembles. Data reduction makes it possible to classify instances belonging to big datasets. We (...) propose to use an agent-based population learning algorithm for data reduction in the feature and instance dimensions. For diversification of the classifier ensembles within the rotation also, alternatively, principal component analysis and independent component analysis are used. The research question addressed in the paper is formulated as follows: does the performance of a classifier using the reduced dataset be improved by integrating the data reduction mechanism with the rotation-based technique and the stacking? (shrink)

We present a framework for verifying systems composed of heterogeneous reasoning agents, in which each agent may have differing knowledge and inferential capabilities, and where the resources each agent is prepared to commit to a goal (time, memory and communication bandwidth) are bounded. The framework allows us to investigate, for example, whether a goal can be achieved if a particular agent, perhaps possessing key information or inferential capabilities, is unable (or unwilling) to contribute more than a given portion (...) of its available computational resources or bandwidth to the problem. We present a novel temporal epistemic logic, BMCL-CTL , which allows us to describe a set of reasoning agents with bounds on time, memory and the number of messages they can exchange. The bounds on memory and communication are expressed as axioms in the logic. As an example, we show how to axiomatise a system of agents which reason using resolution and prove that the resulting logic is sound and complete. We then show how to encode a simple system of reasoning agents specified in BMCL-CTL in the description language of the Mocha model checker (Alur et al., Proceedings of the tenth international conference on computer-aided verification (CAV) , 1998), and verify that the agents can achieve a goal only if they are prepared to commit certain time, memory and communication resources. (shrink)

This paper focuses on studying containment control problem with switching communication graphs of continuous-time heterogeneous multiagent systems where the control inputs are constrained in a nonconvex set. A nonlinear projection algorithm is proposed to address the problem. We discuss the stability and containment control of the system with switching topologies and nonconvex control input constraints under three different conditions. It is shown that all agents converge to the convex hull of the given leaders ultimately while staying in the (...) nonconvex set under the premise that at least one directed path from leaders to the agents exists in each bounded time interval. Finally, the validity of the results obtained in this paper is verified by simulation. (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)

The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the (...) core of the FMSA is similar in both contexts: notions of “levels of system specification”, “behavior of models”, “simulator” and “endomorphic agents” can be partially translated in the terms linked to the “denotational hierarchy” (DH) and recently introduced in a multi-level centered epistemology of M&S. Second, we suggest considering the question of “credibility” of agent M&S in social sciences when we do not try to emulate but only to simulate target systems. Whereas a stringent and standardized treatment of the heterogeneous internal relations (in the DH) between systems of formalisms is the key problem and the essential challenge in the scope of Agent M&S driven engineering, it is urgent too to address the problem of the external relations (and of the external validity, hence of the epistemic power and credibility) of such levels of formalisms in the specific domains of agent M&S in social sciences, especially when we intend to introduce the concepts of activity tracking. (shrink)

The study of imitation and other mechanisms of social learning is an exciting area of research for all those interested in understanding the origin and the nature of animal learning in asocial context. Moreover, imitation is an increasingly important research topic in Artificial Intelligence and social robotics which opens up the possibility ofindividualized social intelligencein robots that are part of a community, and allows us to harness not only individual learning by the single robot, but also the acquisition of new (...) skills by observing other members of the community. After an introduction to the main research issues in research on imitation in various fields, we motivate the particular focus of this work, namely thecorrespondence problem. We describeAction Learning for Imitation via Correspondences between Embodiments, an implemented generic framework for solving the correspondence problem between differently embodied robots. Alice enables a robotic agent to learn a behavioral repertoire suitable to performing a task by observing a model agent. Importantly, the model agent could possibly possess a different type of body, e.g. a different number of limbs or joints, a different height, different sensors, a different basic action repertoire, etc. Previously, in a test-bed where the agents differed according to their possible movement patterns, we demonstrated that the character of imitation achieved will depend on the granularity of subgoal matching, and on the metrics used to evaluate success.In our current work, we implemented Alice in a new test-bed calledRabitwhere simple simulated robotic arm agents use various metrics for evaluating success according to actions, states, effects, or weighted combinations.We examine the roles ofsynchronization,looseness of perceptual matching, and ofproprioceptive matchingby a series of experiments. Also, we study how Alice copes withchanges in the embodimentof the imitator during learning. Our simulation results suggest thatsynchronizationandloose perceptual matchingallow for faster acquisition of behavioral compentencies at low error rates.Social learning plays a role as areplicationmechanism for behaviors and results invariabilitywhen the transmitted behavior differs from the model’s behavior, thus providing theevolutionary substrate for cultureand its pre-cursors. Social learning in robotics could therefore serve as the basis for culture in societies whose members include artificial agents. We address the use of imitative social learning mechanisms like Alice for transmission of skills between robots, and give first examples of transmission of a skill despite differences in embodiment of agents involved. In the particular setup, transmission occurs through a chain, as well as emerging in cyclic arrangements of robots. These simple examples demonstrate that by using social learning and imitation,cultural transmissionis possible among robots, even in heterogeneous groups of robots. (shrink)

The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the (...) core of the FMSA is similar in both contexts: notions of “levels of system specifi cation”, “behavior of models”, “simulator”and “endomorphic agents” can be partially translated in the terms linked to the “denotational hierarchy” (DH) recently introduced in a multi-level centered epistemology of M&S. Second, we suggest considering the question of “credibility” of agent M&S in social sciences when we do not try to emulate but only to simulate target systems. Whereas a stringent and standardized treatment of the heterogeneous internal relations (in the DH) between systems of formalisms is the key problem and the essential challenge in the scope of Agent M&S driven engineering, it is urgent too to address the problem of the external relations (and of the external validity, hence of the epistemic power and credibility) of such levels of formalisms in the specific domains of agent M&S in social sciences, especially when we intend to introduce the concepts of activity tracking. (shrink)

In this article, we show that behavioral features can be obtained at a group level even if they do not appear at the individual level. Starting from a standard model of Pareto optimal allocations, with expected utility maximizers but allowing for heterogeneity among individual beliefs, we show in particular that the representative agent has an inverse S-shaped probability distortion function as in Cumulative prospect theory.

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)

With the rise of the knowledge economy, the knowledge content of goods and services is going up just as their material content is declining. Economic value is increasingly seen to reside in the former - that is, in intangible assets - rather than in the latter. Yet we keep wanting to turn knowledge back into something tangible, something with definite boundaries which can be measured, manipulated, appropriated, and traded. In short, we want to reify knowledge. Scholars have been debating the (...) nature of knowledge since the time of Plato. Many new insights have been gained from these debates, but little theoretical consensus has been achieved. Through six thematically linked chapters, the book articulates the theoretical approach to the production and distribution of knowledge that underpins Max Boisot's conceptual framework, the Information Space or I-Space. In this way the book looks to provide theoretical and practical underpinnings to Boisot's book Knowledge Assets.Following an introductory chapter, how knowledge relates to data and information is first examined in chapter 1, and how different economic actors - entrepreneurs, managers, etc - use knowledge as a basis for action is explored in chapter 2. Chapter 3 looks at how the heterogeneity of economic actors arises naturally from their respective data processing strategies in spite of any similarities in the data that they might share. Chapter 4 argues, contra much transaction-based economics, that an organizational order must have preceded a market order, something that should be reflected in any knowledge-based theory of the firm. Chapter 5 discusses the cultural and institutional significance of different kinds of knowledge flows. Finally, chapter 6 presents an agent-based simulation model, SimISpace, that illustrates how the I-Space might be applied to concrete problems such those of intellectual property rights. A concluding chapter proposes a research agenda based on the theorizing developed in the book.The approach the book sets out is used by a whole range of organizations to issues of knowledge management, policy, economics, and organizational and cultural change. (shrink)

Agent Communication Languages (ACLs) have recently acquired a primary role in open multiagent systems, which need a standard communication framework shared by all interacting heterogeneous agents. According to the most important ACL standard proposals so far, agents are supposed to carry out the communication process by performing actions of a specific type, namely, communicative acts, whose semantics is defined in terms of the agents’ mental states. Although following the mainstream guidelines inspired by the Speech Act Theory, (...) our work illustrates an alternative model of agent communication, by shifting the focus from agents’ mental states to their social state. Taking an existing communicative act library, we provide a semantics for a significant set of acts based on the concept of commitment, and prove that our approach tackles some issues that have not been dealt with in an effective way yet and that may have hindered the rise of an universally accepted ACL standard. (shrink)

Typically, public discussions of questions of social import exhibit two important properties: they are influenced by conformity bias, and the influence of conformity is expressed via social networks. We examine how social learning on networks proceeds under the influence of conformity bias. In our model, heterogeneous agents express public opinions where those expressions are driven by the competing priorities of accuracy and of conformity to one’s peers. Agents learn, by Bayesian conditionalization, from private evidence from nature, and (...) from the public declarations of other agents. Our key findings are that networks that produce configurations of social relationships that sustain a diversity of opinions empower honest communication and reliable acquisition of true beliefs, and that the networks that do this best turn out to be those which are both less centralized and less connected. (shrink)

We consider how an epistemic network might self-assemble from the ritualization of the individual decisions of simple heterogeneous agents. In such evolved social networks, inquirers may be significantly more successful than they could be investigating nature on their own. The evolved network may also dramatically lower the epistemic risk faced by even the most talented inquirers. We consider networks that self-assemble in the context of both perfect and imperfect communication and compare the behaviour of inquirers in each. This (...) provides a step in bringing together two new and developing research programs, the theory of self-assembling games and the theory of network epistemology. (shrink)

A single global authority is not sufficient to regulate heterogenous agents in multiagent systems based on distributed architectures, due to idiosyncratic local situations and to the need to regulate new issues as soon as they arise. On the one hand institutions should be structured as normative systems with a hierarchy of authorities able to cope with the dynamics of local situations, but on the other hand higher authorities should be able to delimit the autonomy of lower authorities to issue (...) valid norms. In this paper, we study the interplay of obligations and strong permissions in the context of hierarchies of authorities using input/output logic, because its explicit norm base facilitates reasoning about norm base maintenance, and it covers a variety of conditional obligations and permissions. We combine the logic with constraints, priorities and hierarchies of authorities. In this setting, we observe that Makinson and van der Torre’s notion of prohibition immunity for permissions is no longer sufficient, and we introduce a new notion of permission as exception and a new distinction between static and dynamic norms. We show how strong permissions can dynamically change an institution by adding exceptions to obligations, provide an explicit representation of what is permitted to the subjects of the normative system and allow higher level authorities to limit the power of lower level authorities to change the normative system. (shrink)

Axiom weakening is a novel technique that allows for fine-grained repair of inconsistent ontologies. In a multi-agent setting, integrating ontologies corresponding to multiple agents may lead to inconsistencies. Such inconsistencies can be resolved after the integrated ontology has been built, or their generation can be prevented during ontology generation. We implement and compare these two approaches. First, we study how to repair an inconsistent ontology resulting from a voting-based aggregation of views of heterogeneous agents. Second, we prevent (...) the generation of inconsistencies by letting the agents engage in a turn-based rational protocol about the axioms to be added to the integrated ontology. We instantiate the two approaches using real-world ontologies and compare them by measuring the levels of satisfaction of the agents w.r.t. the ontology obtained by the two procedures. (shrink)

We provide a logical analysis of private international law, a rather esoteric, but increasingly important, domain of the law. Private international law addresses overlaps and conflicts between legal systems by distributing cases between the authorities of such systems (jurisdiction) and establishing what rules these authorities have to apply to each case (choice of law). A formal model of the resulting interactions between legal systems is proposed based on modular argumentation. It is argued that this model may also be useful for (...) governing the interactions between heterogeneous agents, belonging to different and differently regulated virtual societies, without recourse to a central regulatory agency. The model also provides for multiple interpretations concerning rules of private international law as well as substantive rules of the different legal systems. (shrink)

We study complex phenomena arising from a simple optimal choice consumer model, starting from the classical framework in Benhabib and Day :459–471, 1981). We introduce elements of increasing complexity and we investigate their effects on the resulting social behaviors. The dynamics introduce the dependence of current preferences on past consumers actions. A non-monotone updating preference function allows us to obtain a threshold effect, according to which the agents adopt a bandwagon/snob behavior if the preferences are below/above a certain saturation (...) level. We consider homogeneous and heterogeneous agents and we introduce local/global interaction when they are spatially distributed. We show through simulations several phenomena which are absent in the classical model and which reproduce significant social behaviors, such as path dependence, coexistence of different periodic and chaotic attractors, emergence of spatial patterns. (shrink)