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Search Results: 1 - 10 of 815 matches for " Danko Nikoli? "
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Only T3-AI can reach human-level intelligence: A variety argument
Danko Nikoli
Quantitative Biology , 2015,
Abstract: The recently introduced theory of practopoiesis offers an account on how adaptive intelligent systems are organized. According to that theory biological agents adapt at three levels of organization and this structure applies also to our brains. This is referred to as tri-traversal theory of the organization of mind or for short, a T3-structure. To implement a similar T3-organization in an artificially intelligent agent, it is necessary to have multiple policies, as usually used as a concept in the theory of reinforcement learning. These policies have to form a hierarchy. We define adaptive practopoietic systems in terms of hierarchy of policies and calculate whether the total variety of behavior required by real-life conditions of an adult human can be satisfactorily accounted for by a traditional approach to artificial intelligence based on T2-agents, or whether a T3-agent is needed instead. We conclude that the complexity of real life can be dealt with appropriately only by a T3-agent.
Practopoiesis: Or how life fosters a mind
Danko Nikoli
Quantitative Biology , 2014, DOI: 10.1016/j.jtbi.2015.03.003
Abstract: The mind is a biological phenomenon. Thus, biological principles of organization should also be the principles underlying mental operations. Practopoiesis states that the key for achieving intelligence through adaptation is an arrangement in which mechanisms laying a lower level of organization, by their operations and interaction with the environment, enable creation of mechanisms lying at a higher level of organization. When such an organizational advance of a system occurs, it is called a traverse. A case of traverse is when plasticity mechanisms (at a lower level of organization), by their operations, create a neural network anatomy (at a higher level of organization). Another case is the actual production of behavior by that network, whereby the mechanisms of neuronal activity operate to create motor actions. Practopoietic theory explains why the adaptability of a system increases with each increase in the number of traverses. With a larger number of traverses, a system can be relatively small and yet, produce a higher degree of adaptive/intelligent behavior than a system with a lower number of traverses. The present analyses indicate that the two well-known traverses-neural plasticity and neural activity-are not sufficient to explain human mental capabilities. At least one additional traverse is needed, which is named anapoiesis for its contribution in reconstructing knowledge e.g., from long-term memory into working memory. The conclusions bear implications for brain theory, the mind-body explanatory gap, and developments of artificial intelligence technologies.
An LCD Monitor with Sufficiently Precise Timing for Research in Vision
Peng Wang,Danko Nikoli
Frontiers in Human Neuroscience , 2011, DOI: 10.3389/fnhum.2011.00085
Abstract: Until now, liquid crystal display (LCD) monitors have not been used widely for research in vision. Despite their main advantages of continuous illumination and low electromagnetic emission, these monitors had problems with timing and reliability. Here we report that there is at least one new inexpensive 120 Hz model, whose timing and stability is on a par with a benchmark cathode-ray tube monitor, or even better. The onset time was stable across repetitions, 95% confidence interval (the error) of which was <0.01 ms. Brightness was also delivered reliably across repeated presentations (<0.04% error) and across blocks with different durations (<3% error). The LCD monitor seems suitable for many applications in vision research, including the studies that require combined accuracy of timing and intensity of visual stimulation.
Quantum mechanics needs no consciousness (and the other way around)
Shan Yu,Danko Nikoli
Physics , 2010,
Abstract: It has been suggested that consciousness plays an important role in quantum mechanics as it is necessary for the collapse of wave function during the measurement. Furthermore, this idea has spawned a symmetrical proposal: a possibility that quantum mechanics explains the emergence of consciousness in the brain. Here we formulated several predictions that follow from this hypothetical relationship and that can be empirically tested. Some of the experimental results that are already available suggest falsification of the first hypothesis. Thus, the suggested link between human consciousness and collapse of wave function does not seem viable. We discuss the constraints implied by the existing evidence on the role that the human observer may play for quantum mechanics and the role that quantum mechanics may play in the observer's consciousness.
Distributed Fading Memory for Stimulus Properties in the Primary Visual Cortex
Danko Nikoli,Stefan H?usler,Wolf Singer,Wolfgang Maass
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.1000260
Abstract: It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information in the spiking activity of large ensembles of around 100 neurons. We used sequences of up to three different visual stimuli (letters of the alphabet) presented for 100 ms and with intervals of 100 ms or larger. Most of the information about visual stimuli extractable by sophisticated methods of machine learning, i.e., support vector machines with nonlinear kernel functions, was also extractable by simple linear classification such as can be achieved by individual neurons. New stimuli did not erase information about previous stimuli. The responses to the most recent stimulus contained about equal amounts of information about both this and the preceding stimulus. This information was encoded both in the discharge rates (response amplitudes) of the ensemble of neurons and, when using short time constants for integration (e.g., 20 ms), in the precise timing of individual spikes (≤~20 ms), and persisted for several 100 ms beyond the offset of stimuli. The results indicate that the network from which we recorded is endowed with fading memory and is capable of performing online computations utilizing information about temporally sequential stimuli. This result challenges models assuming frame-by-frame analyses of sequential inputs.
Timescales of Multineuronal Activity Patterns Reflect Temporal Structure of Visual Stimuli
Ovidiu F. Jurju?,Danko Nikoli,Wolf Singer,Shan Yu,Martha N. Havenith,Raul C. Mure?an
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0016758
Abstract: The investigation of distributed coding across multiple neurons in the cortex remains to this date a challenge. Our current understanding of collective encoding of information and the relevant timescales is still limited. Most results are restricted to disparate timescales, focused on either very fast, e.g., spike-synchrony, or slow timescales, e.g., firing rate. Here, we investigated systematically multineuronal activity patterns evolving on different timescales, spanning the whole range from spike-synchrony to mean firing rate. Using multi-electrode recordings from cat visual cortex, we show that cortical responses can be described as trajectories in a high-dimensional pattern space. Patterns evolve on a continuum of coexisting timescales that strongly relate to the temporal properties of stimuli. Timescales consistent with the time constants of neuronal membranes and fast synaptic transmission (5–20 ms) play a particularly salient role in encoding a large amount of stimulus-related information. Thus, to faithfully encode the properties of visual stimuli the brain engages multiple neurons into activity patterns evolving on multiple timescales.
Distributed Fading Memory for Stimulus Properties in the Primary Visual Cortex
Danko Nikoli? equal contributor ,Stefan H?usler equal contributor,Wolf Singer,Wolfgang Maass
PLOS Biology , 2009, DOI: 10.1371/journal.pbio.1000260
Abstract: It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information in the spiking activity of large ensembles of around 100 neurons. We used sequences of up to three different visual stimuli (letters of the alphabet) presented for 100 ms and with intervals of 100 ms or larger. Most of the information about visual stimuli extractable by sophisticated methods of machine learning, i.e., support vector machines with nonlinear kernel functions, was also extractable by simple linear classification such as can be achieved by individual neurons. New stimuli did not erase information about previous stimuli. The responses to the most recent stimulus contained about equal amounts of information about both this and the preceding stimulus. This information was encoded both in the discharge rates (response amplitudes) of the ensemble of neurons and, when using short time constants for integration (e.g., 20 ms), in the precise timing of individual spikes (≤~20 ms), and persisted for several 100 ms beyond the offset of stimuli. The results indicate that the network from which we recorded is endowed with fading memory and is capable of performing online computations utilizing information about temporally sequential stimuli. This result challenges models assuming frame-by-frame analyses of sequential inputs.
Variable Daily Air Temperature Model for Analysis and Design  [PDF]
G. Danko, C. Lu
Applied Mathematics (AM) , 2018, DOI: 10.4236/am.2018.98069
Abstract:
An analytical model, TA(t), for the observed outside air temperature change, Ta(t), with time is developed using two components: one for the variation caused by the Earth’s movement, plus any other quasi-stationary thermodynamic effects due to industrialization; and one for the random variation caused by stochastic and/or chaotic, local environmental changes. The first component, TR(t), describes a regular trend, expressed by periodic functions of time and constants unchanged with time. The second component, TS, is a random, stochastic variation. For the observed outside air temperature, the analytical model of TA(t)=TR(t) +
Time-Dependent Contaminant Transport in Ventilating Air from a Moving Source  [PDF]
George L. Danko, William Asante
Applied Mathematics (AM) , 2017, DOI: 10.4236/am.2017.85054
Abstract: A new method which combines the Eulerian, fixed control volume with a moving, Lagrangean flow channel is described for the solution of the conjugate, advection-diffusion problem for modeling transport processes of contaminant species. The transport model is presented as a conservative mass balance equation in a state-flux, species transport form in the space-time domain. A fully-implicit, general solution scheme is formulated with matrix operators in the space-time domain. The particular solutions for specific initial and boundary conditions and source term are constructed with the help of a single, inverse matrix operator, A-1, which has to be calculated only once for all possible particular problems. Although A-1 involves a large number constants, all are independent from the initial, boundary, and source term input vectors. The multi-level, state-flux, space-time (SFST) scheme brings a significant computational acceleration since A-1 has to be calculated only once, such as in mine ventilation cases involving long drifts with constant air flow velocities. Such application is shown in an example for analyzing the transport and concentration distributions of diesel particulate matter (DPM) in the ventilation air at the working area with the interactions between ventilation and a moving diesel loading machine. Comparison between simulation and in situ DPM monitoring results suggests that reliable evaluation of average exposure of DPM to mine workers may be accomplished directly from tailpipe DPM emission data, ventilation air velocity, and mine geometry with the use of the SFST model even in a highly dynamic working area, potentially reducing the need for real-time DPM monitoring.
Lexical dynamics of the 1990: Numbers and letters
?ipka Danko
Ju?noslovenski Filolog , 2004, DOI: 10.2298/jfi0460099d
Abstract: The author presents the data concerning the Serbo-Croatian lexical dynamics of the 1990s. He notes that the changes in this period were fundamental far-reaching. They left a visible trace not only in the lexicon, but also in the grammatical system of the language. It is interesting to note that despite the popular perception, the new ethnically marked lexical items were characterized by only moderate frequency.
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