This paper, an expanded version of a talk on love given to a literary society, attempts to analyse some of the architectural requirements for an agent which is capable of having primary, secondary and tertiary emotions, including being infatuated or in love. It elaborates on work done previously in the Birmingham Cognition and Affect group, describing our proposed three level architecture (with reactive, deliberative and metamanagement layers), showing how different sorts of emotions relate to those layers. Some of the relationships between emotional states involving partial loss of control of attention (e.g. emotional states involved in being in love) and other states which involve dispositions (e.g. attitudes such as loving) are discussed and related to the architecture. The work of poets and playwrights can be shown to involve an implicit commitment to the hypothesis that minds are (at least) information processing engines. Besides loving, many other familiar states and process...

There is much shallow thinking about emotions, and a huge diversity of definitions of “emotion ” arises out of this shallowness. Too often the definitions and theories are inspired either by a mixture of introspection and selective common sense, or by a misdirected neo-behaviourist methodology, attempting to define emotions and other mental states in terms of observables. One way to avoid such shallowness, and perhaps eventually achieve convergence, is to base concepts and theories on an information processing architecture, which is subject to various constraints, including evolvability, implementability, coping with resource-limited physical mechanisms, and human-like functionality. Within such an architecture-based theory we can distinguish (at least) primary emotions, secondary emotions, and tertiary emotions, and produce a coherent theory which explains a wide range of phenomena and also partly explains the diversity of theories: most theorists focus on only a subset of types of emotions.

A problem which bedevils the study of emotions, and the study of consciousness, is that we assume a shared understanding of many everyday concepts, such as `emotion', `feeling', `pleasure', `pain', `desire', `awareness', etc. Unfortunately, these concepts are inherently very complex, ill-defined, and used with different meanings by different people. Moreover this goes unnoticed, so that people think they understand what they are referring to even when their understanding is very unclear. Consequently there is much discussion that is inherently vague, often at cross-purposes, and with apparent disagreements that arise out of people unwittingly talking about different things. We need a framework which explains how there can be all the diverse phenomena that different people refer to when they talk about emotions and other affective states and processes. The conjecture on which this paper is based is that adult humans have a type of information-processing architecture, with components whi...

In the last decade and a half, the amount of work on affect in general and emotion in particular has grown, in empirical psychology, cognitive science and AI, both for scientific purposes and for the purpose of designing synthetic characters, e.g. in games and entertainments. Such work understandably starts from concepts of ordinary language (e.g. "emotion", "feeling", "mood", etc.). However, these concepts can be deceptive: the words appear to have clear meanings but are used in very imprecise and systematically ambiguous ways. This is often because of explicit or implicit pre-scientific theories about mental states and process. More sophisticated theories can provide a basis for deeper and more precise concepts, as has happened in physics and chemistry. In the Cognition and Affect project we have been attempting to explore the benefits of developing architecture-based concepts, i.e. starting with specifications of architectures for complete agents and then finding out what so...

There are evolutionary trajectories in two different but related spaces, design space and niche space. Co-evolution occurs in parallel trajectories in both spaces, with complex feedback loops linking them. As the design of one species evolves, that changes the niche for others and vice versa. In general there will never be a unique answer to the question: does this change lead to higher fitness? Rather there will be tradeoffs: the new variant is better in some respects and worse in others. Where large numbers of mutually interdependent species (designs) are co-evolving, understanding the dynamics can be very difficult. If intelligent organisms manipulate some of the mechanisms, e.g. by mate selection or by breeding other animals or their own kind, the situation gets even more complicated. It may be possible to show how some aspects of the evolution of human minds are explained by all these mechanisms.

This paper 1 attempts to characterise a unifying overview of the practice of software engineers, AI designers, developers of evolutionary forms of computation, designers of adaptive systems, etc. The topic overlaps with theoretical biology, developmental psychology and perhaps some aspects of social theory. Just as much of theoretical computer science follows the lead of engineering intuitions and tries to formalise them, there are also some important emerging high level cross disciplinary ideas about natural information processing architectures and evolutionary mechanisms and that can perhaps be unified and formalised in the future. 1

This paper discusses some of the requirements for the control architecture of an intelligent human-like agent with multiple independent dynamically changing motives in a dynamically changing only partly predictable world. The architecture proposed includes a combination of reactive, deliberative and meta-management mechanisms along with one or more global \alarm " systems. The engineering design requirements are discussed in relation our evolutionary history, evidence of brain function and recent theories of Damasio and others about the relationships between intelligence and emotions. 1.

At a time of increased social usage of net and collaborative applications a robust and detailed theory of social presence could contribute to our understanding of social behavior in mediated environments, allow researchers to predict and measure differences among media interfaces, and guide the design of new social environments and interfaces. A broader theory of social presence can guide more valid and reliable measures. The article reviews, classifies, and critiques existing theories and measures of social presence. A set of criteria and scope conditions is proposed to help remedy limitations in past theories and measures and to provide a contribution to a more robust theory and measure of social presence. Keywords: Human-computer interaction, computer-mediated communication, nonverbal communication, new media, communication technology, virtual reality

, and inferential coherence. They lack these aspects because their underlying methods have been unable to deal eectively with constituent structure, though more elaborate implementations should overcome this limitation (see, for example, Chalmers 1993). We tend to think of these aspects of thinking as being typically human. This is probably because they were rst studied in relation to language (Katz &Fodor 1963; Chomsky 1959,1965). Human thinking is systematic insofar as people who can understand one sentence (e.g., 869F<uIU 1998 G/9 7n31 F| %-!<%o!<%I!' Aordances, Cognitive Robotics, Consciousness, Frame Problem, Machine Learning, Symbol Grounding 3 Kisokogakubu, Toyonaka, Osaka ")560-8531 John loves Mary) can, in general, understand structurally similar sentences (Mary loves John); it is productive insofar as people can understand and generate an unbounded number of sentences; and i

Research on algorithms and representations once dominated AI. Recently the importance of architectures has been acknowledged, but researchers have different objectives, presuppositions and conceptual frameworks, and this, can lead to confused terminology, argumentation at cross purposes, re-invention of wheels and fragmentation of the research. We propose a methodological framework: develop a representation of a general class of architectures within which different architectures can be compared and contrasted. This should facilitate communication and integration across sub-fields of and approaches to AI, as well providing a framework for evaluating alternative architectures. As a first-draft example we present the CogAff architecture schema, and show how it provides a draft framework. But there is much still to be done.