This technical definition will only make sense toe reader by Ch. 4, once goals and management processes have been described. All that matters forrs section is that a difference between goals and perturbance be noted by the reader. Astate perturbance is not a goal, but it arises out of the processing of goals. In Ch. 7, arelation00 perturbance and "emotion" is discussed. 43 . Sloman says of certain moods that they are "persistent states with dispositional power to color and modify a host of other states and processes. Such moodscan39061-6 be caused by cognitive events with semantic content, though they need not be.[...]0-64000 their control function does not require specific semantic content, though theycan0371-62 cognitive processes that do involve semantic content." (Sloman, 1992b Section 6).A 39642 view is taken in (Oatley, 1992). To be more precise, moods are temporary control stateswhich9881-5 the prominence of some motivators while decreasing others. In particular, they affectthe 41330-5 that certain "goal generators" are triggered. Moreover, moods affect the valenceofce 39476 evaluations, and the likelihood of affective evaluations (perhaps by modifying thresholdsofsholds 42 that trigger evaluations). It is not yet clear whether moods as defined here are9531 - or whether they merely emerge as side-effects of functional processes. . A reflex is a ballistic form of behaviour that can be specified by a narrow setw rules based on input integration and a narrow amount of internal state. There aretwo0981 of reflexes: simple reflexes and fixed action patterns. A simple reflex involves oneaction,-43000 a fixed action pattern involves a collection of actions. Usually, at most only asmall-4120 of perceptual feedback influences reflex action. This would require a definit...

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...

this document. 9.5.2 A comparison of CUE and libido

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.

There are many approaches to the study of mind, and much ambiguity in the use of words like `emotion' and `consciousness'. This paper adopts the design stance and attempts to understand human minds as information processing virtual machines with a complex multi-level architecture whose components evolved at different times and perform different sorts of functions. A multi-disciplinary perspective combining ideas from engineering as well as several sciences helps to constrain the proposed architecture. Variations in the architecture should accommodate infants and adults, normal and pathological cases, and also animals. An analysis of states and processes that each architecture supports provides a new framework for systematically generating concepts of various kinds of mental phenomena. This framework can be used to refine and extend familiar concepts of mind, providing a new, richer, more precise theory-based collection of concepts. Within this unifying framework we hope to explain the ...

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

ABSTRACT 1 This paper discusses agent architectures which are describable in terms of the “higher level ” mental concepts applicable to human beings, e.g. “believes”, “desires”, “intends ” and “feels”. We conjecture that such concepts are grounded in a type of information processing architecture, and not simply in observable behaviour nor in Newell’s knowledge-level concepts, nor Dennett’s “intentional stance. ” A strategy for conceptual exploration of architectures in design-space and nichespace is outlined, including an analysis of design tradeoffs. The SIM AGENT toolkit, developed to support such exploration, including hybrid architectures, is described briefly. Keywords:

Abstract. SIM AGENT is a toolkit that arose out of a project concerned with designing an architecture for an autonomous agent with human-like capabilities. Analysis of requirements showed a need to combine a wide variety of richly interacting mechanisms, including independent asynchronous sources of motivation and the ability to reflect on which motives to adopt, when to achieve them, how to achieve them, and so on. These internal ‘management ’ (and meta-management) processes involve a certain amount of parallelism, but resource limits imply the need for explicit control of attention. Such control problems can lead to emotional and other characteristically human affective states. In order to explore these ideas, we needed a toolkit to facilitate experiments with various architectures in various environments, including other agents. The paper outlines requirements and summarises the main design features of a Pop-11 toolkit supporting both rule-based and ‘sub-symbolic ’ mechanisms. Some experiments including hybrid architectures and genetic algorithms are summarised. 1