59,728 research outputs found
Does intelligence imply contradiction?
Contradiction is often seen as a defect of intelligent systems and a
dangerous limitation on efficiency. In this paper we raise the question of
whether, on the contrary, it could be considered a key tool in increasing
intelligence in biological structures. A possible way of answering this
question in a mathematical context is shown, formulating a proposition that
suggests a link between intelligence and contradiction.
A concrete approach is presented in the well-defined setting of cellular
automata. Here we define the models of ``observer'', ``entity'',
``environment'', ``intelligence'' and ``contradiction''. These definitions,
which roughly correspond to the common meaning of these words, allow us to
deduce a simple but strong result about these concepts in an unbiased,
mathematical manner. Evidence for a real-world counterpart to the demonstrated
formal link between intelligence and contradiction is provided by three
computational experiments.Comment: 39 pages, 6 figures; added Remark 9 (page 19) and Remark 12 (page
25); changed some comments after Definition 13 and in Section 5; some minor
change
How brains make decisions
This chapter, dedicated to the memory of Mino Freund, summarizes the Quantum
Decision Theory (QDT) that we have developed in a series of publications since
2008. We formulate a general mathematical scheme of how decisions are taken,
using the point of view of psychological and cognitive sciences, without
touching physiological aspects. The basic principles of how intelligence acts
are discussed. The human brain processes involved in decisions are argued to be
principally different from straightforward computer operations. The difference
lies in the conscious-subconscious duality of the decision making process and
the role of emotions that compete with utility optimization. The most general
approach for characterizing the process of decision making, taking into account
the conscious-subconscious duality, uses the framework of functional analysis
in Hilbert spaces, similarly to that used in the quantum theory of
measurements. This does not imply that the brain is a quantum system, but just
allows for the simplest and most general extension of classical decision
theory. The resulting theory of quantum decision making, based on the rules of
quantum measurements, solves all paradoxes of classical decision making,
allowing for quantitative predictions that are in excellent agreement with
experiments. Finally, we provide a novel application by comparing the
predictions of QDT with experiments on the prisoner dilemma game. The developed
theory can serve as a guide for creating artificial intelligence acting by
quantum rules.Comment: Latex file, 20 pages, 3 figure
Where Fail-Safe Default Logics Fail
Reiter's original definition of default logic allows for the application of a
default that contradicts a previously applied one. We call failure this
condition. The possibility of generating failures has been in the past
considered as a semantical problem, and variants have been proposed to solve
it. We show that it is instead a computational feature that is needed to encode
some domains into default logic
Do Chatbots Dream of Androids? Prospects for the Technological Development of Artificial Intelligence and Robotics
The article discusses the main trends in the development of artificial intelligence systems and robotics (AI&R). The main question that is considered in this context is whether artificial systems are going to become more and more anthropomorphic, both intellectually and physically. In the current article, the author analyzes the current state and prospects of technological development of artificial intelligence and robotics, and also determines the main aspects of the impact of these technologies on society and economy, indicating the geopolitical strategic nature of this influence. The author considers various approaches to the definition of artificial intelligence and robotics, focusing on the subject-oriented and functional ones. It also compares AI&R abilities and human abilities in areas such as categorization, pattern recognition, planning and decision making, etc. Based on this comparison, we investigate in which areas AI&R’s performance is inferior to a human, and in which cases it is superior to one. The modern achievements in the field of robotics and artificial intelligence create the necessary basis for further discussion of the applicability of goal setting in engineering, in the form of a Turing test. It is shown that development of AI&R is associated with certain contradictions that impede the application of Turing’s methodology in its usual format. The basic contradictions in the development of AI&R technologies imply that there is to be a transition to a post-Turing methodology for assessing engineering implementations of artificial intelligence and robotics. In such implementations, on the one hand, the ‘Turing wall’ is removed, and on the other hand, artificial intelligence gets its physical implementation
Outline of a new approach to the nature of mind
I propose a new approach to the constitutive problem of psychology ‘what is mind?’ The first section introduces modifications of the received scope, methodology, and evaluation criteria of unified theories of cognition in accordance with the requirements of evolutionary compatibility and of a mature science. The second section outlines the proposed theory. Its first part provides empirically verifiable conditions delineating the class of meaningful neural formations and modifies accordingly the traditional conceptions of meaning, concept and thinking. This analysis is part of a theory of communication in terms of inter-level systems of primitives that proposes the communication-understanding principle as a psychological invariance. It unifies a substantial amount of research by systematizing the notions of meaning, thinking, concept, belief, communication, and understanding and leads to a minimum vocabulary for this core system of mental phenomena. Its second part argues that written human language is the key characteristic of the artificially natural human mind. Overall, the theory both supports Darwin’s continuity hypothesis and proposes that the mental gap is within our own species
Reasoning over Ontologies with Hidden Content: The Import-by-Query Approach
There is currently a growing interest in techniques for hiding parts of the
signature of an ontology Kh that is being reused by another ontology Kv.
Towards this goal, in this paper we propose the import-by-query framework,
which makes the content of Kh accessible through a limited query interface. If
Kv reuses the symbols from Kh in a certain restricted way, one can reason over
Kv U Kh by accessing only Kv and the query interface. We map out the landscape
of the import-by-query problem. In particular, we outline the limitations of
our framework and prove that certain restrictions on the expressivity of Kh and
the way in which Kv reuses symbols from Kh are strictly necessary to enable
reasoning in our setting. We also identify cases in which reasoning is possible
and we present suitable import-by-query reasoning algorithms
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