Stevo Bozinovski

SELF-LEARNING AGENTS: A CONNECTIONIST THEORY OF EMOTION BASED ON CROSSBAR VALUE JUDGMENT

This article presents a computational theory of emotions, based on the theory of emotion as value judgment and appraisal. It assumes that what we feel about other people, events, and things, generally indicates how we evaluate them. The basic assumption is that emotion is an internal self-evaluation of something relevant for the existence of the agent, like self-evaluation of the global state the agent is in, and the behavior the agent is about to perform. This work presents an agent architecture which contains the three components of the control system in biological systems?the genetic, neural, and hormonal component. As distillate of the theory, a working architecture that implements value judgment is presented. The architecture is based on a crossbar connectionist adaptive array, which is designed in a way that it computes from the same crossbar memory elements, both emotions toward encountered situations and emotions toward action tendencies. In such a way it actually builds in hardware, inseparable c...

Mental States, EEG Manifestations, and Mentally Emulated Digital Circuits for Brain-Robot Interaction

This paper focuses on electroencephalogram (EEG) manifestations of mental states and actions, emulation of control and communication structures using EEG manifestations, and their application in brain-robot interactions. The paper introduces a mentally emulated demultiplexer, a device which uses mental actions to demultiplex a single EEG channel into multiple digital commands. The presented device is applicable in controlling several objects through a single EEG channel. The experimental proof of the concept is given by an obstacle-containing trajectory which should be negotiated by a robotic arm with two degrees of freedom, controlled by mental states of a human brain using a single EEG channel. The work is presented in the framework of Human-Robot interaction (HRI), specifically in the framework of brain-robot interaction (BRI). This work is a continuation of a previous work on developing mentally emulated digital devices, such as a mental action switch, and a mental states flip-flop.

A new frontier for real-time systems - Lessons from molecular biology

In this paper, we are presenting a bionic approach towards real-time systems research. Observing that a cell is a real-time computing, but also a producing, system, the work presented here explores the analogy between the real-time computer systems (and their management) and the molecular biology control systems. This paper is a further elaboration of the idea that the DNA is indeed a real-time system. It also gives insight into how knowledge obtained from the biological systems could lead to further evolution and improvement of the human-made complex real-time systems.

Controlling Robots Using EEG Signals, Since 1988

The paper considers the emergence of the field of controlling robots using EEG signals. It looks back to the first result in the field, achieved in 1988. From a viewpoint of EEG driven control, it was the first result in controlling a physical object using EEG signals. The paper gives details of the development of the research infrastructure which enabled such a result, including description of the lab setup and algorithms. The paper also gives a description of the scientific context in which the result was achieved by giving a short overview of the first ten papers in the field of EEG driven control.

Real-Time Systems - Biologically Inspired Future

In this paper, we are presenting a bionic approach towards real-time systems research. Observing that a cell is both real-time computing and real-time manufacturing system, the work presented here explores the analogy between the real-time computer systems (and their management) and the molecular biology control systems. This paper is a further elaboration of the idea that the cell is governed by a real-time operating system that resides in the DNA. It also gives insight into how knowledge obtained from the biological systems could lead to further evolution and improvement of the complex human-made real-time systems.

Anticipation Driven Artificial Personality: Building on Lewin and Loehlin

This paper addresses the issue of personality of an animat in terms of anticipation, motivation and emotion. It also discusses some relevant models and theories of personality, and their relation to the consequence driven systems theory. The main result of this work is a fundamental mathematical equation between the emotion, motivation, and behavior. In essence the result can be stated that what motivates an animat behavior is the value of the anticipated emotional consequence of that behavior. Experimental research with an artificial personality architecture is provided, supporting the obtained result.

MEXYS2: A Fuzzy Reasoning Expert System Based on the Subject Emotions Consideration

An expert, system for personality and emotional profile assessment is developed and here reported. The expert knowledge and the basic computational procedure are based on a standard psychological test. Fuzzy reasoning and uncertainty assessment are also features of this system.

Human body parts making: Educational challenges for Engineered Physiology, biorobotics, and biofabrication

This short paper describes a Masters program design to meet the educational demand for body parts making, both from physiological and non-physiological nature (prostheses). The paper gives a new definition of an organ to allow both types of human body parts. It also introduces the concept of Engineered Physiology in the educational system.

Artificial chromosomes as genetic disks: A systems software metaphor for genetic engineering

This paper is a further elaboration on the operating system and systems software metaphor for understanding genetic information processing. Here the focus is on engineering artificial chromosomes: we propose understanding of the process in term of creating genetic files and genetic disks. The paper points out possibilities of using such disks in combination with stem cells for organ engineering. The paper also discusses array of transgenic disks, a human genomic library distributed over colony of bacteria.

Evolving an emotion-based neural control architecture

This work addresses a central problem in evolvable systems - evolution of a neural based emotion integrated learning phenotype from an initial genotype. It describes morphogenesis of a cognitive system based on a neural network, starting from a single genotype having a modulon control structure. It further presents an axon growing mechanism as second step of neural evolution. The neural architecture presented here has the ability to evolve to an emotion integrated neural leaning architecture.