Consciousness and Commonsense Critics in Cognitive Architectures

2012 ◽  
Vol 3 (2) ◽  
pp. 26-37
Author(s):  
K. R. Shylaja ◽  
Vijayakumar Maragal Venkatamuni ◽  
Darryl N. Davis ◽  
E. V. Prasad
Keyword(s):  
Common Sense ◽  
Animal Cognition ◽  
Cognitive Architecture ◽  
Cognitive Architectures ◽  
Reasoning Abilities ◽  
Consciousness Level ◽  
Level Of Consciousness ◽  
Society Of Mind ◽  
Common World

The research identifies the concepts of consciousness and commonsense. It also investigates and demonstrates how consciousness level of an agent and its common sense reasoning abilities can improve the performance and intelligence using SMCA (Society of Mind Cognitive Architecture) as a case study. Consciousness is a sense of awareness about oneself and the surroundings in which the animal or human being lives. This gives a connection between a non materialistic mind and a materialistic brain. Common sense in common world is one that is immediately perceived by everyone from a given environment. A six tiered (layers) SMCA control model is designed that relies on a society of agents operating using metrics associated with the principles of artificial economics in animal cognition. SMCA is a society or collection of agents, where agents tasks implemented on testbed, demonstrates simple to complex level of consciousness and commonsense.

scholarly journals Artificial Minds with Consciousness and Common sense Aspects

2020 ◽  
pp. 1430-1449
Author(s):  
K.R. Shylaja ◽  
M.V. Vijayakumar ◽  
E. Vani Prasad ◽  
Darryl N. Davis
Keyword(s):  
Decision Making ◽  
Energy Level ◽  
Cognitive Processing ◽  
Common Sense ◽  
Cognitive Architecture ◽  
Research Work ◽  
Dynamic Environments ◽  
Consciousness Level ◽  
Common Purpose ◽  
The Common

The research work presented in this article investigates and explains the conceptual mechanisms of consciousness and common-sense thinking of animates. These mechanisms are computationally simulated on artificial agents as strategic rules to analyze and compare the performance of agents in critical and dynamic environments. Awareness and attention to specific parameters that affect the performance of agents specify the consciousness level in agents. Common sense is a set of beliefs that are accepted to be true among a group of agents that are engaged in a common purpose, with or without self-experience. The common sense agents are a kind of conscious agents that are given with few common sense assumptions. The so-created environment has attackers with dependency on agents in the survival-food chain. These attackers create a threat mental state in agents that can affect their conscious and common sense behaviors. The agents are built with a multi-layer cognitive architecture COCOCA (Consciousness and Common sense Cognitive Architecture) with five columns and six layers of cognitive processing of each precept of an agent. The conscious agents self-learn strategies for threat management and energy level maintenance. Experimentation conducted in this research work demonstrates animate-level intelligence in their problem-solving capabilities, decision making and reasoning in critical situations.

A "Society of Mind" Cognitive Architecture Based on the Principles of Artificial Economics

2010 ◽  
Vol 1 (1) ◽  
pp. 51-71 ◽  
Author(s):  
Darryl N. Davis ◽  
Vijayakumar Maragal Venkatamuni
Keyword(s):  
Decision Making ◽  
Control System ◽  
Computational Model ◽  
Cost Function ◽  
Collective Behavior ◽  
Intelligent Agents ◽  
Animal Cognition ◽  
Cognitive Architecture ◽  
Control Model ◽  
Society Of Mind

This research investigates the concept of mind as a control system using the “Society of Agents” metaphor, whereby the whole is described as the collective behavior of simple and intelligent agents. This powerful concept for mind research benefits from the use of metacognition, and eases the development of a self configurable computational model. A six tiered SMCA (Society of Mind Cognitive Architecture) control model is designed that relies on a society of agents operating using metrics associated with the principles of artificial economics in animal cognition. Qualities such as level of decision making, its cost function and utility behavior (the microeconomic level), physiological and goal oriented behavior are investigated. The research builds on current work, and shows the use of affect norms as metacontrol heuristics enables the computational model to adapt and learn in order to optimize its behavior.

scholarly journals Artificial Minds with Consciousness and Common sense Aspects

2017 ◽  
Vol 9 (1) ◽  
pp. 20-42 ◽  
Author(s):  
K.R. Shylaja ◽  
M.V. Vijayakumar ◽  
E. Vani Prasad ◽  
Darryl N. Davis
Keyword(s):  
Decision Making ◽  
Cognitive Processing ◽  
Common Sense ◽  
Cognitive Architecture ◽  
Research Work ◽  
Dynamic Environments ◽  
Artificial Agents ◽  
Consciousness Level ◽  
Common Purpose ◽  
The Common

The research work presented in this article investigates and explains the conceptual mechanisms of consciousness and common-sense thinking of animates. These mechanisms are computationally simulated on artificial agents as strategic rules to analyze and compare the performance of agents in critical and dynamic environments. Awareness and attention to specific parameters that affect the performance of agents specify the consciousness level in agents. Common sense is a set of beliefs that are accepted to be true among a group of agents that are engaged in a common purpose, with or without self-experience. The common sense agents are a kind of conscious agents that are given with few common sense assumptions. The so-created environment has attackers with dependency on agents in the survival-food chain. These attackers create a threat mental state in agents that can affect their conscious and common sense behaviors. The agents are built with a multi-layer cognitive architecture COCOCA (Consciousness and Common sense Cognitive Architecture) with five columns and six layers of cognitive processing of each precept of an agent. The conscious agents self-learn strategies for threat management and energy level maintenance. Experimentation conducted in this research work demonstrates animate-level intelligence in their problem-solving capabilities, decision making and reasoning in critical situations.

Personality-Based Cognitive Design of Characters in Virtual Environments

2016 ◽  
pp. 124-150 ◽  
Author(s):  
Maryam Saberi
Keyword(s):  
Cognitive Architecture ◽  
Emotional Reactions ◽  
Cognitive Architectures ◽  
Reasoning Abilities ◽  
The World ◽  
The One ◽  
Deliberative Reasoning ◽  
High Level ◽  
And Coping ◽  
Different Levels

Personality-based cognitive architectures should yield consistent patterns of behaviour through personality traits that have a modulatory influence at different levels: These factors affect, on the one hand, high-level components such as ‘emotional reactions' and ‘coping behaviour', and on the other hand, low-level parameters such as the ‘speed of movements and repetition of gestures. In our hybrid cognitive architecture, a deliberative reasoning about the world (e.g. strategies and goals of the 3D character) is combined with dynamic real-time response to the environment's changes and sensors' input (e.g. emotional changes). Hybrid system copes dynamically with changes in the environment, and is complicated enough to have reasoning abilities. Designing a cognitive architecture that gives the impression of personality to 3D agents can be a tremendous help making 3D characters more engaging and successful in interactions with humans.

Cognitive architectures and language acquisition: A case study in pronoun comprehension

2010 ◽  
Vol 37 (3) ◽  
pp. 731-766 ◽  
Author(s):  
JACOLIEN VAN RIJ ◽  
HEDDERIK VAN RIJN ◽  
PETRA HENDRIKS
Keyword(s):  
Speech Rate ◽  
Computational Simulation ◽  
Cognitive Architecture ◽  
Cognitive Model ◽  
Poor Performance ◽  
Linguistic Processing ◽  
Cognitive Architectures ◽  
Linguistic Performance ◽  
Do So

ABSTRACTIn this paper we discuss a computational cognitive model of children's poor performance on pronoun interpretation (the so-called Delay of Principle B Effect, or DPBE). This cognitive model is based on a theoretical account that attributes the DPBE to children's inability as hearers to also take into account the speaker's perspective. The cognitive model predicts that child hearers are unable to do so because their speed of linguistic processing is too limited to perform this second step in interpretation. We tested this hypothesis empirically in a psycholinguistic study, in which we slowed down the speech rate to give children more time for interpretation, and in a computational simulation study. The results of the two studies confirm the predictions of our model. Moreover, these studies show that embedding a theory of linguistic competence in a cognitive architecture allows for the generation of detailed and testable predictions with respect to linguistic performance.

Idea generation with Technology Semantic Network

2021 ◽  
pp. 1-19
Author(s):  
Serhad Sarica ◽  
Binyang Song ◽  
Jianxi Luo ◽  
Kristin L. Wood
Keyword(s):  
Engineering Design ◽  
Common Sense ◽  
Semantic Network ◽  
Idea Generation ◽  
Semantic Distance ◽  
The Core ◽  
Design Idea ◽  
Design Ideas ◽  
Design Ideation

Abstract There are growing efforts to mine public and common-sense semantic network databases for engineering design ideation stimuli. However, there is still a lack of design ideation aids based on semantic network databases that are specialized in engineering or technology-based knowledge. In this study, we present a new methodology of using the Technology Semantic Network (TechNet) to stimulate idea generation in engineering design. The core of the methodology is to guide the inference of new technical concepts in the white space surrounding a focal design domain according to their semantic distance in the large TechNet, for potential syntheses into new design ideas. We demonstrate the effectiveness in general, and use strategies and ideation outcome implications of the methodology via a case study of flying car design idea generation.

scholarly journals The liberation of nature and knowledge: a case study on Hans Reichenbach’s naturalism

Synthese ◽  
2021 ◽  
Author(s):  
László Kocsis ◽  
Adam Tamas Tuboly
Keyword(s):  
Common Sense ◽  
Interesting Case ◽  
Valuable Contribution ◽  
Rhetorical Strategy ◽  
Scientific Philosophy ◽  
Political Program ◽  
History Of ◽  
Contemporary Context ◽  
Common Sense Knowledge

AbstractOur main goal in this paper is to present and scrutinize Reichenbach’s own naturalism in our contemporary context, with special attention to competing versions of the concept. By exploring the idea of Reichenbach’s naturalism, we will argue that he defended a liberating, therapeutic form of naturalism, meaning that he took scientific philosophy (or philosophy of nature, Naturphilosophie) to be a possible cure for bad old habits and traditional ways of philosophy. For Reichenbach, naturalistic scientific philosophy was a well-established form of liberation. We do not intend to suggest that Reichenbach acted as an inventor of naturalism; nonetheless, invoking the term and the idea of ‘naturalism’ is more than a simple rhetorical strategy for rehabilitating Reichenbach as a forerunner of this field. We think that his ideas can make a valuable contribution to contemporary debates, and that he presents an interesting case among the other scientifically oriented proponents of his time. After presenting a short reconstruction of the meaning of naturalism—or, more appropriately, naturalisms—in order to be able to correctly situate Reichenbach within his own as well as a systematic context, we discuss Reichenbach’s naturalism against the background of his scientific philosophy, his views on the relation of common-sense knowledge to science, and his efforts at popularization. To delve deeper into this topic, we present a case study to show how Reichenbach argued that in both scientific and philosophical discussions (assuming their naturalistic continuity), it is necessary to move from the request and value of truth to probability. And, finally, we argue that the liberation of knowledge and nature was a socio-political program for Reichenbach, who talked about his own scientific philosophy as “a crusade.” By emphasizing this aspect of Reichenbach’s naturalism, we may be in a better position to situate him in the history of analytic philosophy in general, and in the yet-to-be-written narrative of the naturalistic movement in particular.

scholarly journals Is Science Eliminating Ordinary Talk?

1970 ◽  
Vol 4 (1) ◽  
pp. 25-41
Author(s):  
Louis Caruana
Keyword(s):  
Philosophy Of Science ◽  
Common Sense ◽  
Natural Science ◽  
Philosophy Of Mind ◽  
Science Philosophy ◽  
Actual Operation ◽  
Theories Of Meaning ◽  
Methodology Of Science ◽  
Broad Overview

Discussions dealing with natural science, philosophy and common sense are bound to draw on long-standing debates dealing with realism, methodology of science, philosophy of mind, metaphysics, epistemology, theories of meaning, and other topics. Instead of presenting a broad overview of these main trends, which will necessarily be superficial, I will do a kind of case study. The aim is to present just one particular debate which is of relevance to current research. The presentation is meant to give a taste of how these various long-standing debates are brought to bear on a specific issue. In this way, the very practice of engaging in a particular area of philosophy of science will serve as a platform from where the major areas can be seen in actual operation. The paper has four sections: the nature of ordinary talk; the ontological implications of this; the recently proposed account of the mental; an evaluation.

scholarly journals A Cognitive Computational Model Inspired by the Immune System Response

2014 ◽  
Vol 2014 ◽  
pp. 1-15
Author(s):  
Mohamed Abdo Abd Al-Hady ◽  
Amr Ahmed Badr ◽  
Mostafa Abd Al-Azim Mostafa
Keyword(s):  
Immune System ◽  
Computational Model ◽  
Cognitive Architecture ◽  
Intelligent Agent ◽  
System Response ◽  
Danger Theory ◽  
Proposed Model ◽  
Immune System Response ◽  
Fuzzy State

The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective.

Articulating the Role of Artificial Intelligence in Collective Intelligence: A Transactive Systems Framework

2021 ◽  
Vol 65 (1) ◽  
pp. 670-674
Author(s):  
Pranav Gupta ◽  
Anita Williams Woolley
Keyword(s):  
Artificial Intelligence ◽  
Collective Memory ◽  
Collective Intelligence ◽  
Cognitive Architecture ◽  
Cognitive Resources ◽  
Human Society ◽  
Cognitive Architectures ◽  
The Core ◽  
Systems Framework

Human society faces increasingly complex problems that require coordinated collective action. Artificial intelligence (AI) holds the potential to bring together the knowledge and associated action needed to find solutions at scale. In order to unleash the potential of human and AI systems, we need to understand the core functions of collective intelligence. To this end, we describe a socio-cognitive architecture that conceptualizes how boundedly rational individuals coordinate their cognitive resources and diverse goals to accomplish joint action. Our transactive systems framework articulates the inter-member processes underlying the emergence of collective memory, attention, and reasoning, which are fundamental to intelligence in any system. Much like the cognitive architectures that have guided the development of artificial intelligence, our transactive systems framework holds the potential to be formalized in computational terms to deepen our understanding of collective intelligence and pinpoint roles that AI can play in enhancing it.

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