Refine
Document Type
Language
- English (10) (remove)
Keywords
- cognitive systems (2)
- machine learning (2)
- Cognitive systems (1)
- Computational cognition (1)
- Computational linguistics (1)
- Fock space (1)
- Matlab (1)
- Pope (1)
- Quantum logic (1)
- Semantics processing (1)
Institute
Semantic Dialogue Modeling
(2012)
Machine Semiotics
(2023)
Recognizing a basic difference between the semiotics of humans and machines presents a possibility to overcome the shortcomings of current speech assistive devices. For the machine, the meaning of a (human) utterance is defined by its own scope of actions. Machines, thus, do not need to understand the conventional meaning of an utterance. Rather, they draw conversational implicatures in the sense of (neo-)Gricean pragmatics. For speech assistive devices, the learning of machine-specific meanings of human utterances, i.e. the fossilization of conversational implicatures into conventionalized ones by trial and error through lexicalization appears to be sufficient. Using the quite trivial example of a cognitive heating | device, we show that — based on dynamic semantics — this process can be formalized as the reinforcement learning of utterance-meaning pairs (UMP).
We present a model, inspired by quantum field theory, of the so-called inner stage of technical cognitive agents. The inner stage represents all knowledge of the agent. It allows for planning of actions and for higher cognitive functions like coping and fantasy. By the example of a cognitive mouse agent living in a maze wold, we discuss learning, action planning, and attention in a fully deterministic setting and assuming a totally observable world. We explain the relevance of our approach to cognitive infocommunications.
We present a Matlab toolbox, called “FockBox”, handling
Fock spaces and objects associated with Fock spaces: scalars, ket and
bra vectors, and linear operators. We give brief application examples
from computational linguistics, semantics processing, and quantum logic,demonstrating the use of the toolbox.
The concept of intelligent agents is—roughly speaking—based on an architecture and a set of behavioral programs that primarily serve to solve problems autonomously.
Increasing the degree of autonomy and improving cognitive performance, which can be assessed using cognitive and behavioral tests, are two important research trends. The degree of autonomy can be increased using higher-level psychological modules with which needs and motives are taken into account. In our approach we integrate these modules in architecture for an embodied, enactive multi-agent system, such that distributed problem solutions can be achieved. Furthermore, after uncovering some weaknesses in the cognitive performance of traditionally designed agents, we focus on two major aspects. On the one hand, the knowledge processing of cognitive agents is based on logical formalisms, which have deficiencies in the representation and processing of incomplete or uncertain knowledge. On the other hand, in order to fully understand the performance of cognitive agents, explanations at the symbolic and subsymbolic levels are required. Both aspects can be addressed by quantum-inspired cognitive agents. To investigate this approach, we consider two tasks in the sphere of Shannon's famous mouse-maze problem: namely classifying target objects and ontology inference. First, the classification of an unknown target object in the mouse-maze, such as cheese, water, and bacon, is based on sensory data that measure characteristics such as odor, color, shape, or nature. For an intelligent agent, we need a classifier with good prediction accuracy and explanatory power on a symbolic level. Boolean logic classifiers do work on a symbolic level but are not adequate for dealing with continuous data. Therefore, we demonstrate and evaluate a quantum-logic-inspired classifier in comparison to Boolean-logic-based classifiers. Second, ontology inference is iteratively achieved by a quantum-inspired agent through maze exploration. This requires the agent to be able to manipulate its own state by performing actions and by collecting sensory data during perception. We suggest an algebraic approach where both kinds of behaviors are uniquely described by quantum operators. The agent's state space is then iteratively constructed by carrying out unitary action operators, while Hermitian perception operators act as observables on quantum eigenstates. As a result, an ontology emerges as the simultaneous solution of the respective eigenvalue equations.
Tags: btuktqiai; btuktcogsys; btukttheseus; btuktqtheseus
“[…] the scourge [of AIDS] cannot be overcome by the distribution of condoms: on the contrary, they increase it.”
The statement above by Pope Benedict XVI, at the beginning of his visit to Africa in March 2009, provoked a strong media reaction. It shall be at the centre of our project to apply a technical method for the analysis of dialogue semantics of spoken utterances, already proven in electronic speech signal processing, to communication between the pope and the press. In doing so, the meaning of an utterance beyond the utterance itself is to be found and affixed to subjective relations to reality, which we call “semantic anchors”. The application of such a method stands to reason in the case of cognitive machines whose 'subjective' realities are fully represented in memory contents; an application to the communication between pope and media appears at first glance less obvious, because it is initially not clear to what extent the media can at all be regarded as a “person” with independent cognitive structures. However, we will show in the following that formal methods can be used successfully even in this context, once the appropriate semantic anchors have been established. In doing so, we can also show that the subjective meanings of the pope's statement cited above are, due to the pope’s and press’s completely different discursive realities and the worlds of thought underlying the utterances, incompatible and thus cannot be squared with each other.