The relationship between artificial intelligence and psychological theoriesEr. rahul abhishek
Psychology is one of the parent elements of artificial
intelligence or we can also say that it is the main source for
artificial intelligence. In this paper we are discussing about the
theories of psychology used in AI. Since psychology is the study
of human brain and its nature and AI is the branch which deals
with the intelligence in machine, so for understanding the
intelligence of a machine we have to compare with human
intelligence because AI means the intelligence shown by a
machine like a human being.
Cognitive Neuroscience - Current Perspectives And Approaches Vivek Misra
Cognitive neuroscience is an academic field concerned with the scientific study of biological substrates underlying cognition, with a specific focus on the neural substrates of mental processes. It addresses the questions of how psychological/cognitive functions are produced by neural circuits in the brain.
In current slides, I tried to cover History, Basic Concepts and Research Methods currently used in cognitive neuroscience research.
Continuum of Consciousness
- Controlled and Automatic Processes
- Altered States of Consciousness
- Psychoactive Drugs
- Sleep and Dreams
- Different Stages of Sleep (REM and N-REM)
- 4 Major Questions About Sleep
- Sleep Disorders
- The Unconscious Mind
- Unconsciousness
Talk on artificial consciousness by Ryota Kanai at Consciousness Club in NYC (June 28, 2017). The mission of Araya, Inc. is to understand consciousness by creating it, and apply the insight from consciousness research for designing more human-like AI. We try to address two questions of artificial consciousness: 1. How to create it from functional perspectives, and 2. How to prove consciousness in AI. This talk focusses on the first problem and proposes that the function of consciousness is to generate information, which corresponds to prediction, decoding and data decompression.
The relationship between artificial intelligence and psychological theoriesEr. rahul abhishek
Psychology is one of the parent elements of artificial
intelligence or we can also say that it is the main source for
artificial intelligence. In this paper we are discussing about the
theories of psychology used in AI. Since psychology is the study
of human brain and its nature and AI is the branch which deals
with the intelligence in machine, so for understanding the
intelligence of a machine we have to compare with human
intelligence because AI means the intelligence shown by a
machine like a human being.
Cognitive Neuroscience - Current Perspectives And Approaches Vivek Misra
Cognitive neuroscience is an academic field concerned with the scientific study of biological substrates underlying cognition, with a specific focus on the neural substrates of mental processes. It addresses the questions of how psychological/cognitive functions are produced by neural circuits in the brain.
In current slides, I tried to cover History, Basic Concepts and Research Methods currently used in cognitive neuroscience research.
Continuum of Consciousness
- Controlled and Automatic Processes
- Altered States of Consciousness
- Psychoactive Drugs
- Sleep and Dreams
- Different Stages of Sleep (REM and N-REM)
- 4 Major Questions About Sleep
- Sleep Disorders
- The Unconscious Mind
- Unconsciousness
Talk on artificial consciousness by Ryota Kanai at Consciousness Club in NYC (June 28, 2017). The mission of Araya, Inc. is to understand consciousness by creating it, and apply the insight from consciousness research for designing more human-like AI. We try to address two questions of artificial consciousness: 1. How to create it from functional perspectives, and 2. How to prove consciousness in AI. This talk focusses on the first problem and proposes that the function of consciousness is to generate information, which corresponds to prediction, decoding and data decompression.
Causal emergence and artificial intelligence.pdfLinchuan Wang
Under what circumstances will an aspect arise in software? Generate highscale networks?
If we can answer the above questions, can we also answer the circumstances under which new neurons and the links of new neurons are generated?
Learning Social Affordances and Using Them for PlanningKadir Uyanik
This study extends the learning and use of affordances on robots on two fronts. First, we use the very same affordance
learning framework that was used for learning the affordances of inanimate things to learn social affordances, that is affordances whose existence requires the presence of humans. Second, we use the learned affordances for making multistep
plans.
Specifically, an iCub humanoid platform is equipped with a perceptual system to sense objects placed on a table, as well as the presence and state of humans in the environment, and a behavioral repertoire that consisted of simple object manipulations as well as voice behaviors that are uttered simple verbs. After interacting with objects and humans, the robot learns a set of affordances with which it can make multi-step plans towards achieving a demonstrated goal.
Blue brain enables humans to give new dimensions to science and technology and make enormous development in making the best possible enlightenment to the present scenario.the details can be seen by going though the power point presentation
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
3. Embodied
Cognition
Cognition emerged from the body.
To co-ordinate the body, with a set of structures:
Motor ControlSensory Processing
The activity of the mind is grounded in mechanisms that evolved for
interaction with the environment – that is, mechanisms of sensory processing
and motor control.
4. Cognition
1. Cognition is Situated
2. Cognition is Sensory
Processing
1. Cognition is situated
2. Cognition is time-pressured
3. We off-load cognitive work
onto the environment
4. The environment is part of the
cognitive system
5. Cognition is for action
6. Off-line cognition is body-based
5. Embodied
Consciousness
Dualism Enactivism
Consciousness is not the representation of an existing world.
It is the creation of an imaginary world, as a result of mutual interaction between the
sensorimotor capacities of the organism, its environment, and the history of the
variety of actions that a being in the world performs.
6. Valentino Braitenberg
● 18 June 1926 – 9 September 2011;
● neuroscientist and cyberneticist;
● former director at the Max Planck Institute
for Biological Cybernetics in Tübingen,
Germany;
● most famous book “Vehicles: Experiments in
Synthetic Psychology”, 1984
7. Valentino Braitenberg - Vehicles
“What is cybernetics, what are its
elements?” - Prof. Paul Pangaro
We can think of it as navigation;
Food for thought:
“all intelligent systems have this
property”
8. Valentino Braitenberg - Vehicles
Influenced by his background in cybernetics - a transdisciplinary approach for
exploring regulatory systems—their structures, constraints, and possibilities.
For him, certain structures within animal brains seem interpretable as pieces of
computing machinery because of their simplicity or regularity.
Talks about machines with very simple internal structures and uses psychological
language in describing their behavior.
11. Valentino Braitenberg - Vehicles
The structure of the “network” or system affects directly the resultant behaviour.
The body can be represented as a cybernetic system composed by sensors &
actuators interconnected in multiple ways bringing as a result a simple or complex
physical base and resulting behavior.
Throwback:
“all intelligent systems have this property” - what about the systems/vehicles of
Braitenberg?
Does behavior indicate knowledge or intelligence?
Could cognition actually arise from the properties of the body?
19. Jakob von Uexküll - Umwelt (1934)
perceptual tools = sensors
effector tools = motors
Perceptual
world filled with
perceptual
meanings
Effector world
filled with
operational
meanings
UMWELT
Operators-
interpreters
26. Umwelt - we all live in different times and spaces
● Operational space
● Tactile space
● Visual space
● The farthest plane
Time Space
27. Umwelt
The Umwelt theory states that the mind and the world
are inseparable, because it is the mind that interprets
the world for the organism
Consequently, the Umwelten of different organisms
differ, which follows from the individuality and
uniqueness of the history and biology of every
single organism
33. Homo optimus: modern ideas about Umwelt
We can can play with our system and feed our brain whatever we want)
34. functional information processing modules
Symbol System
Hypothesis
individual behavior generating modules
Physical Grounding
Hypothesis
35. functional information processing modules
it is necessary to combine together many of the
modules to get any behavior
Symbol System
Hypothesis
● Perception & Motors seen as Set of symbols.
● The central system operates over both
interfaces.
● Their meanings are unimportant to the reasoner
● coherence emerges when CS knows the
groundings of the symbols within his or her own
experience.
● Symbols represents entities in the world.
individual behavior generating modules
coexistence and co-operation let more complex
behaviors emerge.
Physical Grounding
Hypothesis
● Each module generates a certain behavior
● necessary to connect it to the world
● express all its goals and desires as physical
action.
● extract all its knowledge from physical sensors.
● make everything explicit.
36. Symbol System Hypothesis
Inadequacy of Simple Symbols
● assume a knowable objective truth
● computations based on these formal systems becomes more and more biologically implausible.
● objectiveness come by adding more complexity turns implausibly.
● frame problem → it is impossible to assume anything that is not explicitly stated
37.
38. the frame problem of Physical grounding Paradigm -> impossible to
represent each interface in the world. ( NP problem)
P vs NP
P → polynomial time solving
NP → non deterministic ( no way to solve it ) time exponential ( easy to
check)
NP -complete → both P & NP Problem ,assumes that solving NP-C,
means that any NP can be solved!
39. Premises:
● Animal Systems → ability to move around in a dynamic environment, sensing the surroundings to a
degree sufficient to achieve the necessary maintenance of life and reproduction.
The Subsumption Architecture:
● computational architecture that enables us to tightly connect perception to action, embedding
robots concretely in the world.
● built on → computation al substrate that is organized into a series of incremental layers
→behavior compiler.
● networks of finite state machines augmented ( AFSM) with timing elements.
● The behavior compiler is machine-independent and compiles into an intermediate file of subsumption
AFSM specifications.
Physical Grounding Hypothesis
40. ● Which one do you think is a more realistic hypothesis ?
Physical Grounding vs Symbol System
41. Verschure (2003)
Perception and behaviour are usually considered separate processes
● Percepual Learning: Constructs compact representation of sensory events,
reflecting the statistical properties independently of behavioural relevance.
● Behavioural Learning: Forms associations between perception and action,
organized through reinforcement.
EXAMPLES
By using mobile robots, he demonstrated that perception and behaviour can
interact synergistically via the environment, through perceptual learning directly
supporting behavioural learning.
42. Mind-Body Relationship
Our moods and thoughts influence our bodies?
When I hear something funny, I smile.
_____________________________________________________________
Our bodies influence our moods and thoughts?
When I smile, that ‘something’ becomes funny.
43. Mind-Body Relationship
Our moods and thoughts influence our bodies?
When I hear something funny, I smile.
_____________________________________________________________
Our bodies influence our moods and thoughts?
When I smile, that ‘something’ becomes funny.
44. Our moods and thoughts influence our bodies
I’m feeling…. HIGH LOW
● Ten feet tall
● Over the moon
● Nothing can bring me down
● On top of the world
● Down in the dumps
● Feeling down
48. Building Non-Embodied Cognition
From Natural Selection to the Homo Sapiens
Artificial Minds... … need artificial Bodies
https://www.youtube.com/watch?v=26fLK9m4eNE&feature=youtu.be
53. The software controls/regulates the
hardware, but it can’t exist without the
hardware. Probably, the hardware
always comes first.
54. The software is there to control the hardware,
but it only exists because the hardware exists.
Probably, the hardware always comes first.
The Cosmos evolves as a set of information patterns
EPOCH 1: Information encoded in atomic structures.
● Software: The laws of Physics. Atomic structure.
● Hardware: Atoms & Molecules.
EPOCH 2: Information encoded in DNA.
● Software: Genotype. Genes, base pairs.
● Hardware: Proteins.
EPOCH 3: Information encoded in neural patters.
● Software: Minds (Brains alive, interacting).
● Hardware: Bodies (perception + motor control).
EPOCH 4: Information encoded in technology.
● Software: Software, code.
● Hardware: Hardware innovation (ex: Robot).
EPOCH 5: Merger of biology and technology.
● Software: Brains + AI.
● Hardware: Bodies (Biological? Robotic?).
Editor's Notes
https://www.youtube.com/watch?v=NDw_1UyNTKI
So let’s go back to humans. We know that we and everything consists of very little micro parts and at the same time we are embedded into the vary large comos. But let’s admit we are not very good at understanding this reality and these scales.
We are trapped in this very thin slice of perception in the middle.
But even there we do not perceive most of the action that is going on.
Take the colors of our world.
There are lightwaves (electromagnetic radiation) that bounces off different objects and hit specialised reseptors at the back of our eyes. But we do not see all the waves out there - in fact what we see is less than 10 trillionth of what is out there.
There are radiowaves, microwaves, X-rays and gamma rays passing through your body right now. There 1000s of cell phones calls going through you. And you are completely unaware of it (if you do not have any super powers and not insane).
Why?
Because you do not have sensors aka biological receptors to pick all this staff up.
But these things are not inherently unseeble:
Snakes include infrared into their reality
Honeybees include ultraviolet in their view of the world
So seems like human’s experience of reality is constrained by our biology. So we cannot assume that our eyes, ears, hands etc give us perception of the objective reality that is out there.
In fact our brain is sampling just a little bit of the world.
The flash-lag effect. When a visual stimulus moves along a continuous trajectory, it may be seen ahead of its veridical position with respect to an unpredictable event such as a punctuate flash.
Seems like differents animals capture different parts of reality:
A blind tick senses almost only temperature and butyric acid.
In the world of black ghost knifefish (cool name) the whole world is colored by electrical fields
For a echolocating bat the reality is constructed of air comprassion waves
There is the word for each slice of reality of each animal. Umwelt - the surrounding world, or self-centered world.. Coined Uexküll in 1934! He imagined it more like some kind of a bubble,
this term is not forgotten, Today such guys like David Eagleman use Umwelt in their pitches to investors and ted-talks and then found companies in Silicon valley)
Presunably each animal assumes that thier Umwelt is an entire objective reality out there.
Ok, so Umwelt is a certain slice of the world: every living creature chooses from the whole variety of colors, sounds, tactile sensations and smells of the world only those stimuli that it can sense and that serve its needs for survival and success.
perceptual world - everything you can sense, generates perceptual meanings or objects of the world
operational world - everything you can effect, use - generates operational meanings for objects of the world
Each functional component (object) of an umwelt has a meaning and so represents the organism's model of the world.
The Umwelt (the model) is not static.
An organism creates and reshapes its own umwelt when it interacts with the world. This is termed a 'functional circle'.
I had taken a young, very intelligent and agile Negro with me from the heart of Africa to Dar-es-Salaam. The only thing which he lacked was a knowledge of European tools. When I bid him climb a short ladder, he asked me: 'How am I to do that, I see nothing but rods and holes?' As soon as another Negro had shown him how to climb the ladder, he could do it easily. From then on, the perceptually given 'rods and holes' held a climbing tone for him, and he recognized them everywhere as a ladder. The receptor image of rods and holes had been supplemented by the effector image of his own action; through this it had acquired a new meaning. The new meaning manifested itself as a new attribute, as a functional or effector tone.
And now let us set into the schema of the functional cycle, the tick as subject, and the mammal as her object. It shows at a glance that three functional cycles follow each other in well-planned succession.
The skin glands of the mammal are the bearers of perceptual meaning in the first cycle, since the stimulus of butyric acid releases specific receptor signs in the tick's receptor organ, and these receptor signs are projected outside as an olfactory cue. By induction (the nature of which we do not know) the processes that take place in the receptor organ initiate corresponding impulses in the effector organ, and these impulses induce the tick to let go with her legs and drop.
The tick, falling on the hairs of the mammal, projects the effector cue of shock onto them. This in turn releases a tactile cue, which extinguishes the olfactory stimulus of the butyric acid. The new receptor cue elicits running about, until it in turn is replaced by the sensation of heat, which starts the boring response.
In the world of man, the functional tones of the objects in a room can be represented by a sitting tone for a chair, a meal tone for the table, and by further adequate effector tones for plates and glasses (eating and drinking tone).
If we represent the recurrent similar functional tones by identical colors in the dog's world, only feeding, sitting, running, and light tones are left. Everything else displays an obstacle tone. .
Finally, for the fly, everything assumes a single running tone, except for the lamp whose significance has already been pointed out, and the crockery on the table
Have you heard of the invisible ships phenomenon?
It goes like this: When Captain Cook/Columbus/Magellan (depending on the version of the story you're hearing) arrived at the coast of Australia/Cuba/South America, the native people completely ignored them, presumably because huge ships were so alien to their experience that "... their highly filtered perceptions couldn't register what was happening, and they literally failed to 'see' the ships." (Quoting here from JZ Knight's What the Bleep Do We Know?)
The best way to find that no two human Umwelten are the same is to have yourself led through unknown territory by someone familiar with it. Your guide unerringly follows a path that you cannot see. Among all the rocks and trees in the environment there are some which, strung together in sequence, stand out as landmarks from all the others, although they are not apparent to a stranger
The familiar path is entirely dependent on the individual subject. It is therefore a typical Umwelt problem.
This gives rise to the widespread conviction that there is only one space and one time for all living things.
Our time is made up of a series of moments, or briefest time units, within which the world shows no change. For the duration of a moment, the world stands still. Man's moment last 1/18 of a second (50 or 60 Hz), a pegeon’ s - 100 Hz
Instead of saying, as heretofore, that without time, there can be no living subject, we shall now have to say that without a living subject, there can be no time.
So what it might mean for us?
Wiener, a mathematician, coined the term 'cybernetics' to denote the study of "teleological mechanisms."
Matter: a change or movement's material cause, is the aspect of the change or movement which is determined by the material that composes the moving or changing things. For a table, that might be wood; for a statue, that might be bronze or marble.
Form: a change or movement's formal cause, is a change or movement caused by the arrangement, shape or appearance of the thing changing or moving. Aristotle says for example that the ratio 2:1, and number in general, is the cause of the octave.
Agent: a change or movement's efficient or moving cause, consists of things apart from the thing being changed or moved, which interact so as to be an agency of the change or movement. For example, the efficient cause of a table is a carpenter, or a person working as one, and according to Aristotle the efficient cause of a boy is a father.
End or purpose: a change or movement's final cause, is that for the sake of which a thing is what it is. For a seed, it might be an adult plant. For a sailboat, it might be sailing. For a ball at the top of a ramp, it might be coming to rest at the bottom.
an acorn's intrinsic telos is to become a fully grown oak tree
Function is befined by structure?
The software is there to control the hardware, but it only exists because the hardware exists. Probably, the hardware always comes first.
The Cosmos evolves as a set of information patterns
EPOCH 1: Information encoded in atomic structures.
Software: The laws of Physics.
Hardware: Atoms & Molecules.
EPOCH 2: Information encoded in DNA.
Software: Genotype. Genes, base pairs.
Hardware: Proteins.
EPOCH 3: Information encoded in neural patters.
Software: Minds (Brains alive, interacting).
Hardware: Bodies (perception + motor control).
EPOCH 4: Information encoded in technology.
Software: Software, code.
Hardware: Hardware innovation (ex: Robot).
EPOCH 5: Merger of biology and technology.
Software: Brains + AI.
Hardware: Bodies (Biological? Robotic?).