scholarly journals A Standard Model of the Mind: Toward a Common Computational Framework across Artificial Intelligence, Cognitive Science, Neuroscience, and Robotics

AI Magazine ◽  
2017 ◽  
Vol 38 (4) ◽  
pp. 13-26 ◽  
Author(s):  
John E. Laird ◽  
Christian Lebiere ◽  
Paul S. Rosenbloom
Keyword(s):  
Artificial Intelligence ◽  
Standard Model ◽  
Cognitive Science ◽  
Reference Point ◽  
International Research ◽  
Research Community ◽  
Computational Framework ◽  
Half Century ◽  
The Mind ◽  
And Robotics

The purpose of this article is to begin the process of engaging the international research community in developing what can be called a standard model of the mind, where the mind we have in mind here is human-like. The notion of a standard model has its roots in physics, where over more than a half-century the international community has developed and tested a standard model that combines much of what is known about particles. This model is assumed to be internally consistent, yet still have major gaps. Its function is to serve as a cumulative reference point for the field while also driving efforts to both extend and break it.

scholarly journals Introduction

2021 ◽  
pp. 1-22
Author(s):  
Sebastian Löbner ◽  
Thomas Gamerschlag ◽  
Tobias Kalenscher ◽  
Markus Schrenk ◽  
Henk Zeevat
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Psychology ◽  
Cognitive Science ◽  
Empirical Investigation ◽  
The Other ◽  
Cognitive Structures ◽  
The Mind ◽  
Empirical Means ◽  
Science Disciplines

AbstractIn order to help to explain cognition, cognitive structures are assumed to be present in the mind/brain. While the empirical investigation of such structures is the task of cognitive psychology, the other cognitive science disciplines like linguistics, philosophy and artificial intelligence have an important role in suggesting hypotheses. Researchers in these disciplines increasingly test such hypotheses by empirical means themselves. In philosophy, the traditional way of referring to such structures is via concepts, i.e. those mental entities by which we conceive reality and with the help of which we reason and plan. Linguists traditionally refer to the cognitive structures as meanings—at least those linguists with a mentalistic concept of meaning do who do not think of meaning as extra-mental entities.

scholarly journals Contribution of Cognitive Science and Artificial Intelligence in the Simulation of the Complex Human Mind

2020 ◽  
Vol 9 (2) ◽  
pp. 928-932
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Real Time ◽  
Human Mind ◽  
Scientific Study ◽  
Computational Procedures ◽  
The Mind ◽  
And Behavior ◽  
Interdisciplinary Theory ◽  
The Brain

The research incorporated encircles the interdisciplinary theory of cognitive science in the branch of artificial intelligence. It has always been the end goal that better understanding of the idea can be guaranteed. Besides, a portion of the real-time uses of cognitive science artificial intelligence have been taken into consideration as the establishment for more enhancements. Before going into the scopes of future, there are many complexities that occur in real-time which have been uncovered. Cognitive science is the interdisciplinary, scientific study of the brain and its procedures. It inspects the nature, the activities, and the elements of cognition. Cognitive researchers study intelligence and behavior, with an emphasis on how sensory systems speak to, process, and change data. Intellectual capacities of concern to cognitive researchers incorporate recognition, language, memory, alertness, thinking, and feeling; to comprehend these resources, cognitive researchers acquire from fields, for example, psychology, artificial intelligence, philosophy, neuroscience, semantics, and anthropology. The analytic study of cognitive science ranges numerous degrees of association, from learning and choice to logic and planning; from neural hardware to modular mind organization. The crucial idea of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures."

A Fundamental Circularity: In the Mind of the Reflective Scientist

2017 ◽  
Author(s):  
Francisco J. Varela ◽  
Evan Thompson ◽  
Eleanor Rosch
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Computer Model ◽  
Philosophy Of Mind ◽  
The Other ◽  
Entire Field ◽  
Sense Of Direction ◽  
The Mind ◽  
Mature Science

This chapter describes cognitive science. In its widest sense, the term cognitive science is used to indicate that the study of mind is in itself a worthy scientific pursuit. At this time, cognitive science is not yet established as a mature science. It does not have a clearly agreed upon sense of direction and a large number of researchers constituting a community. Rather, it is really more of a loose affiliation of disciplines than a discipline of its own. Interestingly, an important pole is occupied by artificial intelligence—thus, the computer model of the mind is a dominant aspect of the entire field. The other affiliated disciplines are generally taken to consist of linguistics, neuroscience, psychology, sometimes anthropology, and the philosophy of mind. Each discipline would give a somewhat different answer to the question of what is mind or cognition, an answer that would reflect its own specific concerns.

General AI

2020 ◽  
pp. 194-206
Author(s):  
Stephen K. Reed
Keyword(s):  
Artificial Intelligence ◽  
Standard Model ◽  
Nobel Prize ◽  
Cognitive Skills ◽  
General Purpose ◽  
Intelligence Tests ◽  
Grand Challenges ◽  
Wide Range ◽  
The Mind

People use their cognitive skills to solve a wide range of problems whereas computers solve only a limited number of specific problems. A goal of artificial intelligence (AI) is to build on its previous success in specific environments to advance toward the generality of human level intelligence. People are efficient general-purpose learners who can adapt to many situations such as navigating in spatial environments and communicating by using language. To compare human and machine reasoning the AI community has proposed a standard model of the mind. Measuring progress in achieving general AI will require a wide variety of intelligence tests. Grand challenges, such as helping scientists win a Nobel prize, should stimulate development efforts.

scholarly journals Conceptual Commitments of the LIDA Model of Cognition

2013 ◽  
Vol 4 (2) ◽  
pp. 1-22 ◽  
Author(s):  
Stan Franklin ◽  
Steve Strain ◽  
Ryan McCall ◽  
Bernard Baars
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Cognitive Functions ◽  
Current Knowledge ◽  
Action Selection ◽  
Theoretical Framework ◽  
General Intelligence ◽  
Artificial General Intelligence ◽  
Level Model ◽  
The Mind

Abstract Significant debate on fundamental issues remains in the subfields of cognitive science, including perception, memory, attention, action selection, learning, and others. Psychology, neuroscience, and artificial intelligence each contribute alternative and sometimes conflicting perspectives on the supervening problem of artificial general intelligence (AGI). Current efforts toward a broad-based, systems-level model of minds cannot await theoretical convergence in each of the relevant subfields. Such work therefore requires the formulation of tentative hypotheses, based on current knowledge, that serve to connect cognitive functions into a theoretical framework for the study of the mind. We term such hypotheses “conceptual commitments” and describe the hypotheses underlying one such model, the Learning Intelligent Distribution Agent (LIDA) Model. Our intention is to initiate a discussion among AGI researchers about which conceptual commitments are essential, or particularly useful, toward creating AGI agents.

scholarly journals MAPF Scenario: Software for Evaluating MAPF Plans on Real Robots

2020 ◽  
Vol 34 (09) ◽  
pp. 13602-13603
Author(s):  
Roman Barták ◽  
Jiří Švancara ◽  
Ivan Krasičenko
Keyword(s):  
Artificial Intelligence ◽  
Computer Games ◽  
Research Community ◽  
Academic Community ◽  
Practical Applications ◽  
Control Programs ◽  
Abstract Version ◽  
Research Platform ◽  
Multi Agent ◽  
And Robotics

Multi-Agent Path Finding (MAPF) deals with finding collision free paths for a set of agents (robots) moving on a graph. The interest in MAPF in the research community started to increase recently partly due to practical applications in areas such as warehousing and computer games. However, the academic community focuses mostly on solving the abstract version of the problem (moving of agents on the graph) with only a few results on real robots. The presented software MAPF Scenario provides a tool for specifying MAPF problems on grid maps, solving the problems using various abstractions (for example, assuming rotation actions or not), simulating execution of plans, and translating the abstract plans to control programs for small robots Ozobots. The tool is intended as a research platform for evaluating abstract MAPF plans on real robots and as an educational and demonstration tool bridging the areas of artificial intelligence and robotics.

scholarly journals El problema de la representación en la filosofía cognitiva

2008 ◽  
Vol 13 ◽  
Author(s):  
Juan C. Vélez
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Point Of View ◽  
Cognitive Systems ◽  
Behavior System ◽  
Andy Clark ◽  
The World ◽  
The Mind

RESUMENLa teoría representacional de la mente, basada en el concepto de representación, ha sido muy criticada, especialmente por recientes enfoques en la ciencia cognitiva, provenientes de la Biología y la Inteligencia Artificial. En este trabajo me centro especialmente en el punto de vista de Francisco Varela, quien sugiere la exclusión del término representación en la explicación de los sistemas cognitivos. Muestro que ello no es necesario, y que hay razones para hablar de representaciones en la relación que tenemos con el mundo en términos de conocimiento, por tanto, el antirrepresentacionalismo de Varela es inadecuado. En ese sentido me parece más afortunada la apreciación que hacen de la ciencia cognitiva y la filosofía de la mente Andy Clark y Pascual Martínez-Freire, y ésta es la postura que defenderé en contra de Varela.PALABRAS CLAVEMENTE, REPRESENTACIÓN, COGNITIVISMO, CONDUCTA, SISTEMAABSTRACTThe representational theory of the mind, based on the concept of representation, has been very criticized, specially by recent approaches to cognitive science, originated from Biology and Artificial Intelligence. In this work I focus my attention specially on the point of view of Francisco Varela, who suggests the exclusion of the term representation in the explanation of cognitive systems. I show that it is unnecessary, and that there are reasons to talk about representations in the relation that we have with the world in terms of knowledge, and therefore, Varela’s antirepresentacionalism is inadequate. In that connection the appreciation that Andy Clark and Pascual Martínez-Freire do of cognitive science and the philosophy of the mind seems more fortunate to me, and this is the position that I will defend against Varela.KEYWORDSMIND, REPRESENTATION, COGNITIVISM, BEHAVIOR, SYSTEM

scholarly journals Building Affordance Relations for Robotic Agents - A Review

2021 ◽  
Author(s):  
Paola Ardón ◽  
Èric Pairet ◽  
Katrin S. Lohan ◽  
Subramanian Ramamoorthy ◽  
Ron P. A. Petrick
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Common Ground ◽  
Direct Transfer ◽  
Research Directions ◽  
Robotic Tasks ◽  
And Robotics

Affordances describe the possibilities for an agent to perform actions with an object. While the significance of the affordance concept has been previously studied from varied perspectives, such as psychology and cognitive science, these approaches are not always sufficient to enable direct transfer, in the sense of implementations, to artificial intelligence (AI)-based systems and robotics. However, many efforts have been made to pragmatically employ the concept of affordances, as it represents great potential for AI agents to effectively bridge perception to action. In this survey, we review and find common ground amongst different strategies that use the concept of affordances within robotic tasks, and build on these methods to provide guidance for including affordances as a mechanism to improve autonomy. To this end, we outline common design choices for building representations of affordance relations, and their implications on the generalisation capabilities of an agent when facing previously unseen scenarios. Finally, we identify and discuss a range of interesting research directions involving affordances that have the potential to improve the capabilities of an AI agent.

scholarly journals The Problem of Meaning in AI and Robotics: Still with Us after All These Years

Philosophies ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 14 ◽  
Author(s):  
Tom Froese ◽  
Shigeru Taguchi
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Deep Neural Networks ◽  
Cognitive Robotics ◽  
Macroscopic Scale ◽  
Enactive Approach ◽  
The Mind ◽  
Synthetic Approaches ◽  
And Robotics ◽  
Made In

In this essay we critically evaluate the progress that has been made in solving the problem of meaning in artificial intelligence (AI) and robotics. We remain skeptical about solutions based on deep neural networks and cognitive robotics, which in our opinion do not fundamentally address the problem. We agree with the enactive approach to cognitive science that things appear as intrinsically meaningful for living beings because of their precarious existence as adaptive autopoietic individuals. But this approach inherits the problem of failing to account for how meaning as such could make a difference for an agent’s behavior. In a nutshell, if life and mind are identified with physically deterministic phenomena, then there is no conceptual room for meaning to play a role in its own right. We argue that this impotence of meaning can be addressed by revising the concept of nature such that the macroscopic scale of the living can be characterized by physical indeterminacy. We consider the implications of this revision of the mind-body relationship for synthetic approaches.

Beérkezett könyvek

2005 ◽  
Vol 60 (3) ◽  
pp. 425-427
Author(s):  
Csaba Pléh
Keyword(s):  
Social Interaction ◽  
Cognitive Science ◽  
Evolutionary Psychology ◽  
Well Being ◽  
General Intelligence ◽  
Human Thought ◽  
Number Of Genes ◽  
History Of ◽  
Origin Of Mind ◽  
The Mind

Ádám György: A rejtozködo elme. Egy fiziológus széljegyzetei Carpendale, J. I. M. és Müller, U. (eds): Social interaction and the development of knowledge Cloninger, R. C.: Feeling good. The science of well being Dunbar, Robin, Barrett, Louise, Lycett, John: Evolutionary psychology Dunbar, Robin: The human story. A new history of makind's evolution Geary, D. C.: The origin of mind. Evolution of brain, cognition and general intelligence Gedeon Péter, Pál Eszter, Sárkány Mihály, Somlai Péter: Az evolúció elméletei és metaforái a társadalomtudományokban Harré, Rom: Cognitive science: A philosophical introduction Horváth György: Pedagógiai pszichológia Marcus, G.: The birth of the mind. How a tiny number of genes creates the complexities of human thought Solso, R. D.: The psychology of art and the evolution of the conscious brain Wray, A. (ed.): The transition to language

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