Social Mental Shaping: Modelling the Impact of Sociality on Autonomous Agents' Mental States

This paper presents a framework that captures how the social nature of agents that are situated in a multi-agent environment impacts upon their individual mental states. Roles and relationships provide an abstraction upon which we develop the notion of social mental shaping. This allows us to extend the standard Belief-Desire-Intention model to account for how common social phenomena (e.g. cooperation, collaborative problem-solving and negotiation) can be integrated into a unified theoretical perspective that reflects a fully explicated model of the autonomous agent's mental state

Artificial Cognition for Social Human-Robot Interaction: An Implementation

© 2017 The Authors Human–Robot Interaction challenges Artificial Intelligence in many regards: dynamic, partially unknown environments that were not originally designed for robots; a broad variety of situations with rich semantics to understand and interpret; physical interactions with humans that requires fine, low-latency yet socially acceptable control strategies; natural and multi-modal communication which mandates common-sense knowledge and the representation of possibly divergent mental models. This article is an attempt to characterise these challenges and to exhibit a set of key decisional issues that need to be addressed for a cognitive robot to successfully share space and tasks with a human. We identify first the needed individual and collaborative cognitive skills: geometric reasoning and situation assessment based on perspective-taking and affordance analysis; acquisition and representation of knowledge models for multiple agents (humans and robots, with their specificities); situated, natural and multi-modal dialogue; human-aware task planning; human–robot joint task achievement. The article discusses each of these abilities, presents working implementations, and shows how they combine in a coherent and original deliberative architecture for human–robot interaction. Supported by experimental results, we eventually show how explicit knowledge management, both symbolic and geometric, proves to be instrumental to richer and more natural human–robot interactions by pushing for pervasive, human-level semantics within the robot's deliberative system

Formal Interpretation of a Multi-Agent Society As a Single Agent

In this paper the question is addressed to what extent the collective processes in a multi-agent society can be interpreted as single agent processes. This question is answered by formal analysis and simulation. It is shown for an example process how it can be conceptualised, formalised and simulated in two different manners: from a single agent (or cognitive) and from a multi-agent (or social) perspective. Moreover, it is shown how an ontological mapping can be formally defined between the two formalisations, and how this mapping can be extended to a mapping of dynamic properties. Thus it is shown how collective behaviour can be interpreted in a formal manner as single agent behaviour.Collective Intelligence, Simulation, Logical Formalisation, Single Vs. Multi-Agent Behaviour

Logic-Based Specification Languages for Intelligent Software Agents

The research field of Agent-Oriented Software Engineering (AOSE) aims to find abstractions, languages, methodologies and toolkits for modeling, verifying, validating and prototyping complex applications conceptualized as Multiagent Systems (MASs). A very lively research sub-field studies how formal methods can be used for AOSE. This paper presents a detailed survey of six logic-based executable agent specification languages that have been chosen for their potential to be integrated in our ARPEGGIO project, an open framework for specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each executable language, the logic foundations are described and an example of use is shown. A comparison of the six languages and a survey of similar approaches complete the paper, together with considerations of the advantages of using logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal "Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe Editor-in-Chie

Towards Learning ‘Self’ and Emotional Knowledge in Social and Cultural Human-Agent Interactions

Original article can be found at: http://www.igi-global.com/articles/details.asp?ID=35052 Copyright IGI. Posted by permission of the publisher.This article presents research towards the development of a virtual learning environment (VLE) inhabited by intelligent virtual agents (IVAs) and modeling a scenario of inter-cultural interactions. The ultimate aim of this VLE is to allow users to reflect upon and learn about intercultural communication and collaboration. Rather than predefining the interactions among the virtual agents and scripting the possible interactions afforded by this environment, we pursue a bottomup approach whereby inter-cultural communication emerges from interactions with and among autonomous agents and the user(s). The intelligent virtual agents that are inhabiting this environment are expected to be able to broaden their knowledge about the world and other agents, which may be of different cultural backgrounds, through interactions. This work is part of a collaborative effort within a European research project called eCIRCUS. Specifically, this article focuses on our continuing research concerned with emotional knowledge learning in autobiographic social agents.Peer reviewe

Agents, idols, and icons

Since the early 1960s, Artificial Intelligence has cherished the ambition to design an artificial cognitive machine able to reproduce intimate aspects of human behaviour. Distributed Artificial Intelligence and its most recent avatars—Multi- Agent Systems—have developed the concept towards social interactions and societal dynamics, attracting the attention of sociologists and ethnographers who found new ways to elaborate or validate their theories. But populations of cognitive agents aren’t the real thing, despite the efforts of their designers. Furthermore, one must cautiously examine the rationale behind these often incredibly complex arrangements of algorithms, in order to assess the usefulness of such exercises. As a matter of fact, Artificial Intelligence relies on a very positivist, and sometimes reductionist, view of human behaviour. For centuries, from Bacon to Pierce, philosophy of mind has provided meaningful insights that challenge some of these views. More recently, post-normal approaches have even taken a more dramatic stand—some sort of paradigm shift—where direct knowledge elicitation and processing override the traditional hardwiring of formal logic-based algorithm within computer agents. Keywords: Agent-Based Modelling, Artificial Intelligence, Icon, Idol, Philosophy of Mind, Cognition

Formal Interpretation of a Multi-Agent Society as a Single Agent

Contains fulltext : 194702.pdf (publisher's version ) (Open Access)In this paper the question is addressed to what extent the collective processes in a multi-agent society can be interpreted as single agent processes. This question is answered by formal analysis and simulation. It is shown for an example process how it can be conceptualised, formalised and simulated in two different manners: from a single agent (or cognitive) and from a multi-agent (or social) perspective. Moreover, it is shown how an ontological mapping can be formally defined between the two formalisations, and how this mapping can be extended to a mapping of dynamic properties. Thus it is shown how collective behaviour can be interpreted in a formal manner as single agent behaviour.23 p

Agent interaction: abstract approaches to modelling, programming and verifying multi-agent systems

Computer systems and their applications are becoming increasingly more complicated. Modern systems often consist of multiple independent parts (hardware and software), which interact with their environment. Computers communicate with other computers, exchange information with and receive commands from their human users and receive information about their physicalor virtual environment. This high degree of interactivity leadsto an inherently larger degree of complexity, which needs to be managed and controlled. An important means to reduce complexity is abstraction. Abstraction meansfinding intuitive concepts to model the complex reality and leaving outunderlying details. In the field of multi-agent systems, in which the work ofthis thesis fits, anthropomorphic abstractions are oftenused. Anagent is an autonomous piece of software, designed and/or built in terms ofanthropomorphic concepts, which interacts with other agents and its environmentin such a way that it takes into account the dynamic circumstances and strives to achieve its aims. In this thesis, we focus on agent interaction. Starting from different viewpoints in the field ofmulti-agent systems, we introduce a number of new abstract concepts for agentinteraction. A danger of using abstraction is that abstract concepts areintroduced without grounding them in the computational reality. Therefore, wetake care to always relate our abstract notions to lower-level concepts. We start in Chapter 2 by anchoring three already existing and popular agentconcepts, which are belief, desire and intention, in externally observableagent behaviour. We provide criteria which formally describe when behaviour of an agent indicates that the agent has a certainmental state (a belief, desire or intention). These criteria can be used by agents themselves to attribute belief, desire and intention to other agents, onthe basis of observed behaviour. Chapter 3 deals with agent verification. As the complexity of agent systems ishigh, verification of these systems is very difficult. We develop two principleswhich aid in making verification of agent systems more manageable. The firstprinciple is language abstraction. We use two logical languages to phraseproperties, an abstract one and a detailed one. Properties in theabstract language are shorter and more intuitive than properties in thedetailed language. The second principle is constructing abstract, generic,reusable systems of properties and proofs. In Chapter 4 we present a new model of agents, which focuses on agentinteraction. Our model explicitly includes the dynamic environment. We have areal-time model: actions have a duration. This means that actions of one or more agents can takeplace during overlapping time frames, leading to harmful interference orbeneficial synergy. Agents can perform group actions, which means that themembers of the group perform individual actions in a coordinated manner. In Chapter 5, we develop the programming language GrAPL (Group AgentProgramming Language), intended to program multi-agent systems in which agentscan form temporary alliances to perform group actions. Before a group actions isperformed, the agents communicate with each other to pose demands on details ofthe action and the composition of the group of actors. The programming languagehas a formal operational semantics. We generalise the idea of Chapter 5 in Chapter 6, by looking at group plansinstead of group actions. A group plan is a composed action, consisting of bothindividual actions and group actions, which are partially ordered in time. Weprovide a new high-level coordination language which heterogeneous agents canuse to discuss group plans and to execute them in a synchronised manner

The Mechanistic and Normative Structure of Agency

I develop an interdisciplinary framework for understanding the nature of agents and agency that is compatible with recent developments in the metaphysics of science and that also does justice to the mechanistic and normative characteristics of agents and agency as they are understood in moral philosophy, social psychology, neuroscience, robotics, and economics. The framework I develop is internal perspectivalist. That is to say, it counts agents as real in a perspective-dependent way, but not in a way that depends on an external perspective. Whether or not something counts as an agent depends on whether it is able to have a certain kind of perspective. My approach differs from many others by treating possession of a perspective as more basic than the possession of agency, representational content/vehicles, cognition, intentions, goals, concepts, or mental or psychological states; these latter capabilities require the former, not the other way around. I explain what it means for a system to be able to have a perspective at all, beginning with simple cases in biology, and show how self-contained normative perspectives about proper function and control can emerge from mechanisms with relatively simple dynamics. I then describe how increasingly complex control architectures can become organized that allow for more complex perspectives that approach agency. Next, I provide my own account of the kind of perspective that is necessary for agency itself, the goal being to provide a reference against which other accounts can be compared. Finally, I introduce a crucial distinction that is necessary for understanding human agency: that between inclinational and committal agency, and venture a hypothesis about how the normative perspective underlying committal agency might be mechanistically realized

Directional adposition use in English, Swedish and Finnish

Directional adpositions such as to the left of describe where a Figure is in relation to a Ground. English and Swedish directional adpositions refer to the location of a Figure in relation to a Ground, whether both are static or in motion. In contrast, the Finnish directional adpositions edellä (in front of) and jäljessä (behind) solely describe the location of a moving Figure in relation to a moving Ground (Nikanne, 2003). When using directional adpositions, a frame of reference must be assumed for interpreting the meaning of directional adpositions. For example, the meaning of to the left of in English can be based on a relative (speaker or listener based) reference frame or an intrinsic (object based) reference frame (Levinson, 1996). When a Figure and a Ground are both in motion, it is possible for a Figure to be described as being behind or in front of the Ground, even if neither have intrinsic features. As shown by Walker (in preparation), there are good reasons to assume that in the latter case a motion based reference frame is involved. This means that if Finnish speakers would use edellä (in front of) and jäljessä (behind) more frequently in situations where both the Figure and Ground are in motion, a difference in reference frame use between Finnish on one hand and English and Swedish on the other could be expected. We asked native English, Swedish and Finnish speakers’ to select adpositions from a language specific list to describe the location of a Figure relative to a Ground when both were shown to be moving on a computer screen. We were interested in any differences between Finnish, English and Swedish speakers. All languages showed a predominant use of directional spatial adpositions referring to the lexical concepts TO THE LEFT OF, TO THE RIGHT OF, ABOVE and BELOW. There were no differences between the languages in directional adpositions use or reference frame use, including reference frame use based on motion. We conclude that despite differences in the grammars of the languages involved, and potential differences in reference frame system use, the three languages investigated encode Figure location in relation to Ground location in a similar way when both are in motion. Levinson, S. C. (1996). Frames of reference and Molyneux’s question: Crosslingiuistic evidence. In P. Bloom, M.A. Peterson, L. Nadel & M.F. Garrett (Eds.) Language and Space (pp.109-170). Massachusetts: MIT Press. Nikanne, U. (2003). How Finnish postpositions see the axis system. In E. van der Zee & J. Slack (Eds.), Representing direction in language and space. Oxford, UK: Oxford University Press. Walker, C. (in preparation). Motion encoding in language, the use of spatial locatives in a motion context. Unpublished doctoral dissertation, University of Lincoln, Lincoln. United Kingdo