The Mind as a Control System

Sloman, Aaron

doi:10.1017/s1358246100002460

Cited by 52 publications

(42 citation statements)

References 4 publications

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“…But insofar as biological organisms are to a large extent control systems (Wiener, 1961), or more generally information-processing systems, finding out what they do as controllers or as information processors is a very different task from observing physical behaviour, whether internal or external (Sloman, 1993;Sloman and Chrisley, 2003). 1 That is because the most important components of an information processor may be components of virtual machines rather than physical machines.…”

Section: Non-physical Aspects Of Organisms and Their Environmentsmentioning

confidence: 99%

More things than are dreamt of in your biology: Information-processing in biologically inspired robots

Sloman

Chrisley

2005

Cognitive Systems Research

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Animals and robots perceiving and acting in a world require an ontology that accommodates entities, processes, states of affairs, etc., in their environment. If the perceived environment includes information-processing systems, the ontology should reflect that. Scientists studying such systems need an ontology that includes the first-order ontology characterising physical phenomena, the second-order ontology characterising perceivers of physical phenomena, and a (recursive) third order ontology characterising perceivers of perceivers, including introspectors. We argue that second-and third-order ontologies refer to contents of virtual machines and examine requirements for scientific investigation of combined virtual and physical machines, such as animals and robots. We show how the CogAff architecture schema, combining reactive, deliberative, and meta-management categories, provides a first draft schematic third-order ontology for describing a wide range of natural and artificial agents. Many previously proposed architectures use only a subset of CogAff, including subsumption architectures, contention-scheduling systems, architectures with 'executive functions' and a variety of types of 'Omega' architectures. Adding a multiply-connected, fast-acting 'alarm' mechanism within the CogAff framework accounts for several varieties of emotions. H-CogAff, a special case of CogAff, is postulated as a minimal architecture specification for a human-like system. We illustrate use of the CogAff schema in comparing H-CogAff with Clarion, a well known architecture. One implication is that reliance on concepts tied to observation and experiment can harmfully restrict explanatory theorising, since what an information processor is doing cannot, in general, be determined by using the standard observational techniques of the physical sciences or laboratory experiments. Like theoretical physics, cognitive science needs to be highly speculative to make progress.

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Section: Non-physical Aspects Of Organisms and Their Environmentsmentioning

confidence: 99%

More things than are dreamt of in your biology: Information-processing in biologically inspired robots

Sloman

Chrisley

2005

Cognitive Systems Research

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“…Later we'll distinguish desire-like, belief-like and other sorts of functional states (Sloman, 1993). The label 'affective' as generally understood seems to be very close to this notion of a desire-like state, and subsumes a wide variety of more specific types of affective states, including the subset we'll define as 'emotional'.…”

Section: Needs Functions and Functional Statesmentioning

confidence: 96%

“…Examples include states in which possibilities are contemplated, but neither desired nor believed, for instance in planning, or in purposeless day-dreaming (imagination-like and plan-like states (Sloman, 1993)) or some kinds of artistic activities. Such activities have requirements that overlap with requirements for producing belief-like and desire-like states.…”

Section: Affective Vs Non-affective (What To Do Vs How Things Are)mentioning

confidence: 99%

The Architectural Basis of Affective States and Processes

Sloman¹,

Chrisley²,

Scheutz³

2005

Who Needs Emotions?

Self Cite

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Much discussion of emotions and related topics is riddled with confusion because different authors use the key expressions with different meanings. Some confuse the concept of "emotion" with the more general concept of "affect", which covers other things besides emotions, including moods, attitudes, desires, preferences, intentions, dislikes, etc. Moreover researchers have different goals: some are concerned with understanding natural phenomena, while others are more concerned with producing useful artifacts, e.g. synthetic entertainment agents, sympathetic machine interfaces, and the like. We address this confusion by showing how "architecture-based" concepts can extend and refine our pre-theoretical concepts in ways that make them more useful both for expressing scientific questions and theories, and for specifying engineering objectives. An implication is that different information-processing architectures support different classes of emotions, different classes of consciousness, different varieties of perception, and so on. We start with high level concepts applicable to a wide variety of types of natural and artificial systems, including very simple organisms, namely concepts such as "need", "function", "information-user", "affect", "informationprocessing architecture". For more complex architectures, we offer the CogAff schema as a generic framework which distinguishes types of components that may be in a architecture, operating concurrently with different functional roles. We also sketch H-Cogaff, a richlyfeatured special case of CogAff, conjectured as a type of architecture that can explain or replicate human mental phenomena. We show how the concepts that are definable in terms of such architectures can clarify and enrich research on human emotions. If successful for the purposes of science and philosophy the architecture is also likely to be useful for engineering purposes, though many engineering goals can be achieved using shallow concepts and shallow theories, e.g., producing "believable" agents for computer entertainments. The more human-like robot emotions will emerge, as they do in humans, from the interactions of many mechanisms serving different purposes, not from a particular, dedicated "emotion mechanism".

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“…To put it in slightly more abstract terms, we strongly suspect (along with Brooks, many biologists, and increasing numbers of cognitive scientists (Sloman, 1993)) that useful control systems to generate interesting behavior in autonomous robots will necessarily involve many emergent interactions between the constituent parts (even though there may be hierarchical functional decomposition within some of these parts). However, we go further by claiming that there is no evidence that humans are capable of designing systems with these characteristics using traditional analytical approaches.…”

Section: Why Evolve?mentioning

confidence: 99%

Artificial Evolution: A New Path for Artificial Intelligence?

Husbands

Harvey

Cliff

et al. 1997

Brain and Cognition

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Recently there have been a number of proposals for the use of artificial evolution as a radically new approach to the development of control systems for autonomous robots. This paper explains the artificial evolution approach, using work at Sussex to illustrate it. The paper revolves around a case study on the concurrent evolution of control networks and visual sensor morphologies for a mobile robot. Wider intellectual issues surrounding the work are discussed, as is the use of more abstract evolutionary simulations as a new potentially useful tool in theoretical biology.

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The Mind as a Control System

Cited by 52 publications

References 4 publications

More things than are dreamt of in your biology: Information-processing in biologically inspired robots

More things than are dreamt of in your biology: Information-processing in biologically inspired robots

The Architectural Basis of Affective States and Processes

Artificial Evolution: A New Path for Artificial Intelligence?

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