Chapter 1 - Cognitive Sciences: One or Many?

Question 1

“crisis in psychology,”

Answer 1

The ‘crisis in psychology’ was an idea from the 1920s that psychology was not a unified field,
but had instead fragmented into very different,
competing schools of thought. This phrase
was originated by Bühler in the 1920s.

It is important to cognitive science because
while cognitive science was unified when it
began in the 1950s, modern cognitive science
seems fragmented into very different schools
of thought (classical, connectionist,
embodied). In other words, cognitive science
may be experiencing its own crisis.

Question 2

note the existence of three main approaches within
the cognitive science discipline; what makes them distinct from one another?

Answer 2

Classical cognitive science, connectionist cognitive science, and embodied cognitive science,
- They have dramatically different views about what the term ‘information’ processing means

Question 3

Pluralistic Discipline Meaning

Answer 3

In general, a pluralistic discipline is a field of study or area of knowledge that encompasses multiple perspectives, approaches, or methodologies. This can include different theories, schools of thought, or methods of inquiry that are used to understand and investigate a particular subject. Pluralistic disciplines often involve the integration of different viewpoints and approaches, rather than a single dominant perspective or ideology.
- Psychology is fated to be enormously fragmented

Question 4

Psychology Original POV (prior to fragmentation)

Answer 4

The object of interest (consciousness) can be studied experimentally.

When psychology originated, the promise of a new, unified science was fuelled by the view that a coherent object of enquiry (conscious experience) could be studied using a cohesive paradigm (the experimental method).

Question 5

Cognitive Science Metaphor

Answer 5

A metaphor for cognitive science could be the “brain as a computer.”
- compares the mind and mental processes to a computer, suggesting that the brain is a kind of information-processing system that takes in input, processes it, and produces output in the form of thoughts, behaviours, and actions.
- used to describe various cognitive processes, such as perception, memory, and decision-making, and has been influential in the development of computational models of the mind.

Question 6

Methodological pluralism

Answer 6

Methodological pluralism involves finding value in a variety of sources of information, including believing that no research method is inherently superior to any other; the idea that there is no single “best” or most appropriate method for studying a particular phenomenon, and that multiple methods can be used to understand and investigate a subject.
- increase the robustness and validity of findings, as it allows researchers to triangulate their results and to confirm or disconfirm their hypotheses using multiple lines of evidence.

Question 7

In what ways is cognitive psychology associated with methodological pluralism

Answer 7

Methodological pluralism is often associated with cognitive psychology because of the wide range of methods that are used in the field.
- variety of approaches and methods in order to understand the complex processes that underlie cognition, and they may use multiple methods in combination in order to gain a more complete understanding of how the mind works.
- cognitive psychology is often seen as an interdisciplinary field, with researchers coming from a variety of backgrounds and using different approaches and methodologies to study the mind.

Question 8

How is cognitive science a cohesive paradigm

Answer 8

• The mind can be understood as a kind of information-processing system and that mental processes can be studied and explained using computational models and other techniques.
• The integration of multiple perspectives and approaches. Cognitive science is an interdisciplinary field that draws on various disciplines (pluralistic approach)

Question 9

information processors require explanations from three different levels, which are:

Answer 9

Information processors, such as computers or other computational systems, can be understood and analyzed at different levels of abstraction. These levels of abstraction correspond to different ways of thinking about the system and how it works, and each level provides a different level of detail and explanation. They are:
- computational level
- algorithmic level
- implementational level

Introduced by Marr

Question 10

Computational Level

Answer 10

The computational level refers to the overall function or goal of the system and the way in which it processes and manipulates information in order to achieve this goal. At the computational level, we might describe the input and output of the system, the operations it performs on the data, and the algorithms it uses to process the information.
- formal proofs

Question 11

Algorithmic level

Answer 11

The algorithmic level refers to the specific steps or procedures that are used to implement the computation or function of the system. At this level, we might describe the specific operations that are carried out on the data, the sequence in which they are performed, and the rules or logic that govern their execution.
- build computer programs to do something

Question 12

implementational level

Answer 12

The implementational level refers to the physical instantiation of the system, including the hardware and software components that make up the system and the way in which these components are organized and interact with one another. At the implementational level, we might describe the specific hardware and software components of the system, the way in which they are connected and arranged, and the way in which they interact with one another to perform the computation or function of the system.

The instantiation principle, the idea that in order for a property to exist, it must be had by some object or substance; the instance being a specific object rather than the idea of it.

Question 13

Apply the computational, algorithmic, and implementational levels to perception

Answer 13

For example, consider the mental process of perception.
- At the computational level, we might describe the goal of perception as being to extract and interpret relevant information from the environment in order to guide behaviour.
- At the algorithmic level, we might describe the specific steps or procedures involved in perception, such as sensation, attention, and interpretation.
- At the implementational level, we might describe the neural mechanisms that underlie these processes, such as how sensory input is encoded in the brain and how it is transformed and processed as it moves through different brain areas.

Question 14

Describe ‘Cognitive Science’ definitions

Answer 14

Definitions of cognitive science usually emphasize cooperation across disciplines.

Question 15

According to cybernetics, the mind and body should be viewed as:

Answer 15

According to cybernetics, the mind and body should be viewed as a single system embedded in and interacting with the environment.
- That mental processes are not abstract and disconnected from the world but are instead deeply rooted in the sensory, motor, and perceptual systems of the body and the structures of the environment.
- This perspective suggests that the mind and the body are not separate systems that operate independently but are deeply interconnected and that mental processes arise from the dynamic interaction between the body, the environment, and the brain.
- Agents are adaptively linked to their environment.

Question 16

What is The Information Processing Hypothesis

Answer 16

The human mind is a complex system that receives, stores, retrieves, transforms and transmits information similar to computers and other information-processing systems.

The information processing hypothesis is a theory that suggests that the mind can be understood as a kind of information-processing system. This theory suggests that the mind takes in information from the environment through the senses, processes it in some way, and produces output in the form of thoughts, behaviors, and actions. The information processing hypothesis is based on the idea that the mind operates according to a set of rules or principles that are similar to those used by computers and other information-processing systems.

Question 17

What is Boolean Logic and how is is related to the brain?

Answer 17

In boolean logic, statements are represented using the binary values true and false (also represented as 1 and 0, respectively). Boolean logic uses a set of logical operators (such as AND, OR, and NOT) to combine these statements in order to form more complex logical expressions. Boolean logic is based on the principles of truth tables, which provide a way of determining the truth value of a logical expression based on the truth values of its component statements.

The brain was assumed to be digital, because the all-or-none generation of an action potential was interpreted as being equivalent to assigning a truth value in a Boolean logic

Question 18

can you describe how information processors require explanations at the computational, algorithmic, and implementational levels

Answer 18

Information processors, such as computers or other computational systems, can be understood and analyzed at different levels of abstraction:

The computational level refers to the overall function or goal of the system and the way in which it processes and manipulates information in order to achieve this goal. At the computational level, we might describe the input and output of the system, the operations it performs on the data, and the algorithms it uses to process the information.

The algorithmic level refers to the specific steps or procedures that are used to implement the computation or function of the system. At this level, we might describe the specific operations that are carried out on the data, the sequence in which they are performed, and the rules or logic that govern their execution.

The implementational level refers to the physical instantiation of the system, including the hardware and software components that make up the system and the way in which these components are organized and interact with one another. At the implementational level, we might describe the specific hardware and software components of the system, the way in which they are connected and arranged, and the way in which they interact with one another to perform the computation or function of the system.

Question 19

Thinking Artifacts: Expert Systems

Answer 19

Thinking artifacts are artificial intelligence (AI) systems that are designed to perform tasks that require thinking or reasoning, such as decision-making, problem-solving, and learning.
- designed to mimic the decision-making processes of a human expert
- often involve decision trees

Question 20

Well-posed Problems

Answer 20

A well-posed problem is a problem that is clearly defined and has a clear solution.
- Classical cognition uses this a lot
- By using well-posed problems, cognitive scientists can be sure that they are testing a specific aspect of cognition, rather than being influenced by other factors that might affect performance.
- For example, if a cognitive scientist is studying memory, they might use a well-posed problem such as a list of words that a participant needs to remember. By using a well-posed problem, the cognitive scientist can be sure that they are only studying the participant’s memory, rather than being influenced by other factors such as attention or problem-solving skills.

Classical cognitive science is a field of study that focuses on understanding how the human mind works and how it processes information. In order to study the mind and its processes, cognitive scientists often use well-posed problems as a way to test and evaluate different theories and models of cognition.

Question 21

Classical Cognitive Approach Critique(s) (FOUR)

Answer 21

• OVERSIMPLIFIES: One criticism of the classical cognitive approach is that it tends to oversimplify the mind and reduce cognitive processes to a series of discrete steps or stages. This can be problematic because it ignores the complexity and context-dependence of many cognitive processes.
• ASSUMES MIND IS PASSIVE: Another criticism is that the classical cognitive approach often assumes that the mind is a passive information processor rather than an active and embodied system interacting with the environment. This can lead to an incomplete understanding of how the mind works and how the body and the environment influence it.
• DOES NOT CONSIDER EXTERNAL/CULTURAL/SOCIAL FACTORS: Other criticisms of the classical cognitive approach include its focus on individual cognitive processes rather than social and cultural factors, its reliance on experimental methods that may not accurately capture real-world cognitive processes, and its lack of attention to emotional and affective factors that can influence cognition.
• CANNOT MANAGE ILL-POSED PROBLEMS: Many abilities that humans are experts at without training, such as speaking, seeing, and walking, seemed to be beyond the grasp of classical cognitive science. These abilities involve dealing with ill-posed problems. For example: Not successful in fields such as speech recognition, language translation, or computer vision.

Question 22

Ill-posed Problems

Answer 22

An ill-posed problem is deeply ambiguous, has poorly defined knowledge and goal states, and involves poorly defined operations for manipulating knowledge. As a result, it is not well suited to classical analysis, because a problem space cannot be defined as an ill-posed problem.

This suggests that the digital computer provides a poor definition of the kind of information processing performed by humans.

Question 23

What does the phrase “biological vacuum” refer to?

Answer 23

Connectionist cognitive science views the mind as an emergent property of the brain’s neural networks rather than as a separate entity that exists independently of the brain. As such, connectionists reject the idea of a “biological vacuum,” or a mind independent of the brain and its biology. Instead, they argue that cognitive processes are fundamentally rooted in the brain’s neural networks and are shaped by the brain’s anatomy, chemistry, and physiology.

Question 24

Artificial Neural Network

Answer 24

An artificial neural network is a system of simple processors analogous to neurons, which operate in parallel and send signals to one another via weighted connections that are analogous to synapses.
- Signals detected by input processors are converted into a response that is represented as activity in a set of output processors.
- Connection weights determine the input-output relationship mediated by a network, but they are not programmed. Instead, a learning rule is used to modify the weights. Artificial neural networks learn from by Example.

An artificial neural network is a computational model inspired by the structure and function of the neural networks found in the brain.
- Neural networks are composed of a large number of simple processing units called neurons, which are connected together in a way that allows them to process information. Neural networks are able to learn and adapt by adjusting the strengths of the connections between their neurons based on the input they receive.
- Artificial neural networks have been use to model a wide range of ill-posed problems.

Question 25

Physical symbol system

Answer 25

Symbolic systems are those in which information is represented and processed using explicit, symbolic representations, such as words, numbers, and logical symbols. In contrast, subsymbolic systems are those in which information is represented and processed in a more distributed or implicit manner without using explicit symbolic representations. A physical symbol system has sufficient means for general intelligent action.
- Key idea for classical cognitive sciences
- Entities in the world are represented in the mind with symbols (does not need to be physical entities (e.g., laws, word)
- I.e., just like how a variable in algebra can substitute for a number, a symbol can substitute for a real world thing.

Question 26

Symbol Manipulation (Examples)

Answer 26

Manipulating symbols can mean
- Applying rules: If my cousin calls me, I let it go to voicemail (This is a production rule because the “if-part” is followed by an action)
- Applying logic to propositions

Question 27

Propostion (Example)

Answer 27

All humans like chocolate.
* Alona is a human.
* From these, we can use logic to infer that Alona likes chocolate

What if Alona does not like chocolate?
What if I tell you that Rufus likes chocolate?
Can we infer that Rufus is a human?

Question 28

“Parallel processing in the brain” Meaning

Answer 28

Processes in the brain can be described as parallel in the sense that they involve the simultaneous activation and processing of information by multiple brain regions or neural pathways.
- The brain is a highly distributed system, and many mental processes involve the simultaneous activation and processing of information by a number of different brain regions.
- This parallel processing allows the brain to perform complex cognitive tasks efficiently, and it enables the rapid integration and integration of information from multiple sources.

• There is evidence that many mental processes, including perception, attention, learning, and memory, involve the parallel processing of information by multiple brain regions.
• For example, research on perception has shown that different brain regions are specialized for processing different types of sensory information, and that these regions work together in parallel to extract and interpret the relevant features of the environment. Similarly, research on learning and memory has suggested that different brain regions are involved in different stages of learning and memory formation, and that these regions work together in parallel to encode and store new information.

Question 29

Classical Cognitive Science

Answer 29

• Classical cognitive science sees cognition as the rule-governed manipulation of symbols. Within the classical tradition, mental processes such as perception, attention, learning, memory, and decision-making are understood in terms of manipulating symbolic representations using logical rules.
• It is inspired by the digital computers of the 20th century
• It’s key idea is the physical symbol system
• Its key architectures are the Turing machine, the von Neumann machine, and the production system

Classical cognitive science is a perspective within cognitive science that emerged in the 1950s and 1960s and is characterized by the use of symbolic models to represent and reason about mental processes. The classical approach is based on the idea that the mind can be understood as a kind of symbolic system, in which mental representations are encoded in symbolic form and processed using logical rules.
- the study of processing digital computers gave birth to classical cog. science
- There is a classical distinction between structure and process, in which a distinct set of explicit rules is manipulated by discrete symbols stored in a separate memory.

Question 30

Physical Symbol System Hypothesis

Answer 30

Some physical symbol systems have the capacity for intelligence

Question 31

Perceptrons

Answer 31

Simple artificial neural networks that were not programmed but instead learned from example.Perceptrons are composed of a single layer of artificial neurons, and they are used to classify patterns or input data into different categories based on the characteristics of the input.
- connectionist cog science
- Perceptrons are able to learn by adjusting the weights of the connections between their neurons based on the input they receive.

They are used to model a wide range of cognitive and behavioral phenomena, including perception, attention, learning, and decision-making. Perceptrons are particularly useful for tasks that involve binary classification, such as distinguishing between different types of objects in an image or identifying spam emails.

While perceptrons are a simple and intuitive model of artificial neural networks, they have a number of limitations. In particular, perceptrons are only able to classify patterns that are linearly separable, meaning that they cannot be used to classify patterns that are more complex or that require more sophisticated decision-making strategies

Question 32

Connectionist Cognitive Science

Answer 32

The POV is that cognition emerges from multiple, simultaneous, and simple processes. The key idea is that there is PARALLEL DISTRIBUTE PROCESSING—still information processing, but not like the classical digital computer.
- Connectionism abandoned the notion of rules, symbols, and digital information processing
- Inspired by brains architecture (rooted in the biology of the brain )
- Simple processes implemented via artificial neurons

Key architectures include:
- perceptron
- multi-layered perception
- autoassociative network

Connectionists argued that the problem with the
classical notion of information processing was that it ignored the fundamental properties of the brain. Connectionism cast itself as a neuronally inspired, biologically plausible alternative to classical cognitive science.
- Connectionist models of cognition are based on the idea that cognitive processes emerge from the dynamic interactions of neurons within these networks rather than being mediated by a central processing unit or “homunculus.”
- Processes of the brain were described as subsymbolic and parallel (parallel, i.e., the brain is viewed as a distributed system in which problem solutions emerged from the parallel activity of a large number of simple processors: a network was both structure and process, and networks both stored and modified information at the same time).

Question 33

Why is the rise of connectionism in Cognitive Science important

Answer 33

Represented the fragmentation of cognitive scicnede; distint school of thought from classical cognitive science

Question 34

Why is the rise of connectionism in Cognitive Science important?

Answer 34

Represented the fragmentation of cognitive science, as it is a distinct school of thought from classical cognitive science. Connectionist cognitive science arose because it felt that classical cognitive science did not pay sufficient attention to a particular part of the body, the brain.

It also provided a new perspective on the mind and has led to a number of important insights into the way the mind works. It has also inspired new mental-process modelling approaches and has had several practical applications.

Question 35

Embodied Cognitive Science

Answer 35

Replaced classical emphasis on planning with a new emphasis n action. Led to the “new robotics” and the notion of the extended mind. POV: Cognition emerges from structured relations between an agent and its world
- Inspired by replacing planning with acting
- Key ideas: situatedness and embodiment
- Key architectures are behaviour-based robots
- Embodied cognitive science critiques both classical and connectionist approaches because both ignore the whole body and its interaction with the world.
- Abandons methodological solipsism, which is reflected in the sense-think-act cycle that characterizes both classical and connectionist cognitive science
- Radical versions of embodied cognitive science aim to dispense with METAL REPRESENTATIONS completely and argue that the mind extends outside the brain, into the body and the world
- Embodied cognitive science views the brain as a controller, not as a planner
- the extended mind, the emphasis on action, and
the abandonment of representation,

Embodied cognitive science is a perspective within cognitive science that emphasizes the role of the body and the environment in shaping and constraining mental processes. This perspective is based on the idea that the mind and the body are not separate entities, but are instead deeply intertwined and that the body and the environment play a critical role in shaping the way in which the mind works.

Question 36

Methodological Solipsism

Answer 36

Methodological solipsism is a term that is used to describe the idea that the mind can only be studied by looking at its INTERNAL STATES and processes and that the external world and the body do not play a role in shaping or constraining mental processes.
- Critiques representational states
- Methodological solipsism is often associated with the classical approach to cognitive science, which emphasizes the use of symbolic models to represent and reason about mental processes.
- reflected in the sense-think-act cycle that characterizes both classical and connectionist cognitive science.

Question 37

Describe “representational states” according to methodological solipsism

Answer 37

• According to methodological solipsism, representational states are mental states that are characterized by the presence of symbolic representations. They are thought to be central in shaping and constraining mental processes.
• Representational states are thought to be the fundamental units of mental representation. They are used to encode and manipulate information in a way that allows the mind to perform complex cognitive tasks.
• Within the classical perspective, representational states are mental states characterized by the presence of symbolic representations.

Question 38

Representational State Examples

Answer 38

An example of a representational state might be the mental representation of a particular concept, such as the concept of a “dog.” According to the classical approach to cognitive science, the concept of a dog would be represented in the mind as a symbolic representation, such as a word or a mental image. This symbolic representation would be stored in a representational state, and it would be used to encode and manipulate information about dogs, such as their appearance, behavior, and characteristics.

Other examples of representational states might include the mental representation of a particular object, such as a chair, or the mental representation of a particular event, such as a birthday party. In each case, the mental representation of the object or event would be encoded in a symbolic form and stored in a representational state, and it would be used to encode and manipulate information about the object or event in question.

Question 39

Sense-think-act Cycle

Answer 39

Also known as the classical sandwich. The sense-think-act cycle is a model of cognitive processing that describes the way in which the mind processes information and generates behavior. According to this model, cognitive processing can be divided into three stages: sensing, thinking, and acting.
- Methodological solipsism is reflected in the sense-think-act cycle that characterizes both classical and connectionist cognitive science.
- Both classical and connectionist cognitive science adopt the sense-think-act cycle because both have representations standing between perceptual inputs and behavioural outputs.

Question 40

Sense-think-act Cycle: Sense

Answer 40

In the sensing stage, the mind receives and processes information from the environment through the sensory systems of the body. This information is used to generate a representation of the environment and to update the internal model of the world that is stored in memory.

Question 41

Sense-think-act Cycle: Think

Answer 41

In the thinking stage, the mind uses the representation of the environment and the internal model of the world to generate a plan or decision about how to act. This process involves the manipulation of symbolic representations and the application of logical rules.

Question 42

Sense-think-act Cycle: Act

Answer 42

In the acting stage, the mind translates the plan or decision into behavior by activating the appropriate muscles and movements through the motor system of the body. This behavior is then carried out in the environment, and the cycle begins again as the mind senses the consequences of its actions and updates its internal model of the world.

Question 43

How is the “sense-think-act cycle” applied according to the “connectionist” perspective?

Answer 43

Connectionist approaches to cognitive science can use the sense-think-act cycle as a framework for understanding the way in which the mind processes information and generates behavior. In this context, the sense-think-act cycle can be understood as a way of describing the way in which the brain processes information from the environment, generates plans or decisions, and activates the appropriate muscles and movements in order to carry out actions.

According to connectionist approaches to cognitive science, the sense-think-act cycle is implemented through the activation and processing of patterns of neural activity within the brain. The brain receives and processes information from the environment through the sensory systems of the body, and this information is used to update the internal model of the world that is stored in memory. The brain then generates plans or decisions by activating and processing patterns of neural activity that encode these plans or decisions, and these plans or decisions are translated into behavior through the activation of the appropriate muscles and movements through the motor system of the body.

Question 44

Sense-act Cycle (NOT SENSE-THINK-ACT CYCLE)

Answer 44

The sense-act cycle is a model of cognitive processing that describes the way in which the mind processes information and generates behavior. According to this model, cognitive processing can be divided into two stages: sensing and acting.
- Sense-act processing abandons planning in particular and the use of representations in general.

The sense-act cycle is similar to the sense-think-act cycle, but it does not include the intermediate stage of thinking or decision-making. According to the sense-act cycle, the mind directly translates the representation of the environment and the internal model of the world into behavior, without the need for intermediate steps such as the manipulation of symbolic representations or the application of logical rules.

Question 45

Sense-act Cycle: Sense

Answer 45

In the sensing stage, the mind receives and processes information from the environment through the sensory systems of the body. This information is used to generate a representation of the environment and to update the internal model of the world that is stored in memory.

Question 46

Sense-act Cycle: Act

Answer 46

In the acting stage, the mind translates the representation of the environment and the internal model of the world into behavior by activating the appropriate muscles and movements through the motor system of the body. This behavior is then carried out in the environment, and the cycle begins again as the mind senses the consequences of its actions and updates its internal model of the world.

Question 47

Why does embodied cognitive science view the brain as a controller, not a planner?

Answer 47

According to the embodied perspective in cognitive science, the brain should be viewed as a controller rather than as a planner because the mind and the body are deeply intertwined, and mental processes arise from the dynamic interaction between the body, the environment, and the brain.

This perspective suggests that the brain is not a central planner that generates abstract symbolic representations and manipulates them using logical rules. Instead, it is a controller that coordinates the activity of the body and the environment to achieve specific goals or objectives.

Question 48

What does it mean when cybernetics says, “agents are adaptively linked to their environment?”

Answer 48

When cybernetics says that agents are adaptively linked to their environment, it means that agents (such as animals, humans, or artificial systems) are able to interact with and adapt to their environment in order to achieve specific goals or objectives.e

According to the principles of cybernetics, agents should be viewed as open systems that are embedded in and interact with their environment, and that their behavior is shaped by this interaction. Agents are able to sense their environment and use this information to update their internal models of the world, and they are able to generate and execute plans or decisions in order to achieve specific goals or objectives.

The concept of adaptive linking refers to the idea that agents are able to adapt their behavior to their environment in order to achieve their goals or objectives. This process involves the continuous feedback and adjustment of behavior based on the consequences of actions, and it allows agents to adapt to changing or uncertain environments in order to achieve their goals.

Overall, the idea that agents are adaptively linked to their environment is central to the principles of cybernetics and it has been influential in shaping our understanding of the way in which agents (such as animals, humans, or artificial systems) interact with and adapt to their environment.

Question 49

Gibson’s Theory of Direct Perception

Answer 49

Gibson’s theory of direct perception is a theory of perception that emphasizes the role of the environment in shaping perception and the idea that perception is an active process of exploring and interpreting the environment. This theory was proposed by James J. Gibson, an American psychologist who is known for his contributions to the study of perception and the psychology of perception.

According to Gibson’s theory of direct perception, perception is not a passive process of registering sensory stimuli, but is instead an active process of exploring and interpreting the environment. Perception involves the detection of patterns of information in the environment and the use of this information to update the internal model of the world that is stored in memory.

Gibson argued that the information needed for perception is provided directly by the structure of the environment and that this information is available to the perceiver without the need for additional cognitive processing. He proposed that the environment provides information in the form of affordances, which are the opportunities that the environment offers for action, and that perception involves the detection and interpretation of these affordances.

In Gibson’s theory of direct perception, affordances are the opportunities that the environment offers for action. According to this theory, the environment provides information in the form of affordances, and perception involves the detection and interpretation of these affordances.

Question 50

What does “affordances” refer to in Gibson’s Theory of Direct Perception?

Answer 50

In Gibson’s theory of direct perception, affordances are the opportunities that the environment offers for action. According to this theory, the environment provides information in the form of affordances, and perception involves the detection and interpretation of these affordances.

Affordances are a key concept in Gibson’s theory of direct perception, and they are thought to play a central role in shaping perception and guiding behavior. Affordances are not properties of the objects in the environment, but are instead properties of the relationship between the objects and the perceiver. They are the opportunities that the environment offers for action, such as the opportunity to sit on a chair or to grasp a handle.

Gibson argued that affordances are directly perceivable and that they are an important source of information for perception and action. He proposed that the perception of affordances is an automatic and effortless process that does not require additional cognitive processing or the use of abstract symbolic representations.

Overall, the concept of affordances is central to Gibson’s theory of direct perception and it has been influential in shaping our understanding of the way in which the environment shapes perception and guides behavior.

Question 51

What is an example of “affordances” in Gibson’s Theory of Direct Perception?

Answer 51

An example of affordances in Gibson’s theory of direct perception might be the opportunity to sit on a chair. According to this theory, the chair affords sitting, which is an opportunity for action that is provided by the structure of the chair and the relationship between the chair and the perceiver.

In this example, the chair provides information about its function and how it can be used through the structure of the chair and the relationship between the chair and the perceiver. The chair’s structure (such as its shape, size, and materials) provides information about its ability to support the weight of a person and the range of positions that are possible for sitting. The relationship between the chair and the perceiver provides information about the distance and orientation of the chair relative to the perceiver, and the effort required to reach and interact with the chair.

Overall, this example illustrates how affordances are properties of the relationship between the objects in the environment and the perceiver, and how they provide information about the opportunities that the environment offers for action.

Question 52

Extended Mind Hypothesis

Answer 52

• embodied cognitive science

The extended mind hypothesis is a theory in the philosophy of mind that suggests that the mind is not limited to the boundaries of the brain, but can extend into the environment and the body. This theory challenges the traditional view that the mind is a separate and distinct entity that is located inside the brain, and it suggests that the mind can be extended into the environment and the body through the use of external resources such as tools, symbols, and other technologies.

According to the extended mind hypothesis, the mind should be viewed as a distributed system that is not limited to the brain, but can extend into the environment and the body. This perspective suggests that the mind is not a separate and abstract system that operates independently of the body and the environment, but is instead deeply rooted in the sensory, motor, and perceptual systems of the body and the structures of the environment.

A consequence of the extended mind is cognitive scaffolding, where the abilities of “classical” cognition are enhanced by using the external world as support.

Question 53

The Extended Mind Example

Answer 53

Otto & Igna go to the museum
* Otto has Alzheimer’s and so he writes down the directions
to the museum in his notebook
* Igna is able to remember the directions
* Both Otto and Igna can successfully navigate to the
museum. They both believe that they know how to get
there, but Otto depends on a worldly device to function
as part of his memory.
* Part of Otto’s mind resides outside of his skin, in the world

Question 54

Cognitive Scaffolding according to the Extended Mind Hypothesis

Answer 54

According to the extended mind hypothesis, cognitive scaffolding is the use of external resources such as tools, symbols, and other technologies to shape and constrain mental processes. This perspective suggests that the mind can be extended into the environment and the body through the use of these external resources, and that the use of these resources can facilitate or scaffold cognitive processes such as perception, attention, learning, and decision-making.

Cognitive scaffolding is based on the idea that the mind is a distributed system that is not limited to the brain, but can extend into the environment and the body. This perspective suggests that the mind is not a separate and abstract system that operates independently of the body and the environment, but is instead deeply rooted in the sensory, motor, and perceptual systems of the body and the structures of the environment.

Question 55

Examples of “cognitive scaffolding”

Answer 55

Using a calculator to perform complex mathematical calculations: The use of a calculator can scaffold or support the process of performing complex mathematical calculations by providing a tool that can perform these calculations more efficiently and accurately than would be possible using mental effort alone.

Using a map to navigate an unfamiliar city: The use of a map can scaffold or support the process of navigating an unfamiliar city by providing a visual representation of the layout of the city and the locations of important landmarks and destinations.

Using a spreadsheet to organize and analyze data: The use of a spreadsheet can scaffold or support the process of organizing and analyzing data by providing a tool that can store and manipulate data in a structured and organized manner.

Using a smartphone to access information and communicate with others: The use of a smartphone can scaffold or support the process of accessing information and communicating with others by providing a portable device that can connect to the internet and facilitate communication with others through various applications and services.

Question 56

Seminal publications of modern
experimental psychology

Answer 56

• Fechner’s 1860 Elements of
  Psychophysics
• Wundt’s (1873) Principles of
  Physiological Psychology

Question 57

Why might psych. look interdisciplinary in cases when it is it not?

Answer 57

Specialized and fractured
* “Psychologists often ignore work
outside their own laboratories,
usually ignore work outside their
own sub-specialties, and almost
always ignore work outside their own
discipline” (Gilbert, 2002, p. 3). - a reason why it might not be interdisciplinary
- if they do not communicate, it doesn’t count

Question 58

Content vs. Foundations of Psychology

Answer 58

• Trained psychologists may study content areas,
  rather than foundational assumptions.
• Often Psych classes are structured around content,
  not foundational assumptions
• UAlberta PSYCH Class examples:
• Infant and Child development
• Cultural Psychology
• Human Memory
• Spatial Cognition
• Language
• Perception
• Others?

Question 59

Foundational Assumptions

Answer 59

1. Brains are information processors (computers), so
   thought can be mechanized - So prevalent that it’s hard to recognize E.g. storage and retrieval in memory research
   - classical cognitive science
2. Brains are like neural networks, which can learn (spawned connections)
   - neural networks do not have a central processor
   - pdp models
3. The mind extends beyond the brain, and studying the
   brain in isolation is meaningless

Question 60

Simon & Newel

Answer 60

• asked people to think out loud as they solved tasks
• then programmed computers to do the same actions,
  and thus solve the task
• mechanizing thought that computers can then be programmed to execute

Question 61

Linguistics (Noam Chomsky)

Answer 61

Provided structure and algorithm to linguistics (previously
a descriptive field)
* Showed that the structure/algorithm was shared across
languages
* Evidence of 1. shared hardware (obviously) and 2. shared innate computational modules

Question 62

Symbol

Answer 62

Entities in the world are represented in the mind with
symbols
- Need not be physical entities - e.g. laws, words
- Like a variable in algebra can substitute for a number
- X = Y - 3
- Y = 5
- … a symbol can substitute for a real world thing

Question 63

Physical Symbol System

Answer 63

• A physical symbol system manipulates these symbols
• E.g. reason about entities and rules.
• Computers are an example of a physical symbol
  system, and we will see other examples soon!
• Physical Symbol System Hypothesis: some physical
  symbol systems have the capacity for intelligence

Question 64

Origin of Machine Learning

Answer 64

• Roots in AI (comes form psychology)

Question 65

Types of Machine Learning

Answer 65

Theme: how can i make the best predictions based on my data?
ML is generally divided into:
1) Supervised Learning
* Using a set of labelled data, predict the label
2) Unsupervised Learning
* Using unlabeled data, find the groups of data points that
“belong together”
3) Reinforcement Learning
* Using positive and negative feedback, train a model to
perform a task

Question 66

Supervised Learning

Answer 66

• Requires a training set
• Given a collection of data (training set): Each data sample has features, one of which is the class label

Question 67

Training Set

Question 68

Components of Learning

Answer 68

Memory – memorize the data exactly and use them to determine an answer/scenario
* Averaging – learn a simple summary of the data and use them to determine an answer/scenario; one strategy would be to predict the majority outcome.
* Generalization – learn to use the data in a more
complex way that (hopefully!) works better for new
examples

Question 69

Memory Example

Answer 69

memorize the data exactly and use them to determine an answer/scenario

Question 70

Noisy Data

Answer 70

There might be another variable affecting the data.

Question 71

Averaging Example

Answer 71

One strategy would be to predict the majority outcome.

Question 72

Generalization Example

Answer 72

Dealing with previously unseen cases;

Question 73

Decision Trees

Answer 73

Predict by splitting on attribute values

Question 74

Entropy Chart

Answer 74

Entropy is a measure of disorder. Also called amount of information.
* The higher the entropy, the messier the box of labels
* The lower the entropy, the purer the box of labels

Question 75

How are “Decision Trees” an example of Mechanizing Thought?

Answer 75

Recall Newell and Simon attempted to mechanize thought
by having people explain their thought processes
* Essentially: have people tell us their internal decision tree!
* Learning a decision tree allows us to infer the decisions
using data

Decision trees are a very simple example of machine
learning, but they illustrate machine learning’s main ideas
that apply to many models

Question 76

How are “Decision Trees” an example of Classical Cog. Science?

Answer 76

• Rule based reasoning!
• Each datapoint is a symbolic representation of
  something from the real world
• Leslie Kaelbling’s example in MIT courseware): data is the days

Question 77

Turing Test

Answer 77

Problems: 70s, a rule-based system (decision tree to impersonate a therapist, therefore, they would reflect back to the person and ask neutral questions)

Question 78

Chinese Room Thought Experiment