Cognitive Lecture 10

AI: Artificial Intelligence
Recursive: Working on something in a loop to achieve new results repeatedly
Domain: An area of knowledge or skill
Abnormality: Something unusual, derived from the prefix "ab-" indicating absence of normalcy
Diagnostic: A process or tool that aids in identifying diseases or conditions

Understanding cognition is limited by the inability to measure thought directly.
The brain focuses on the most noticeable and familiar information for perception.
Prioritization of identification and action is crucial for brain function.
Language is a unique trait of humans.
Generalizations, narratives, and schemas help simplify complex information.
Attention acts as a filtering mechanism between perception and cognition.
Psychologists focus on deliberate memorization techniques.
Long-term memory is multifaceted and well-researched.
Decision-making models have shown versatility.
Observing individuals at their best provides valuable insights.

Problem: A situation that obstructs goal achievement.
- Cannot always rely on learned or habitual solutions.
- Novel solutions are often necessary.

Well-defined problems:
- Clear goals.
- Definable options for solving.
- Methods available to measure solution quality.
- Examples include puzzles and games.
Ill-defined problems:
- Goals and options are ambiguous; quality of solutions is hard to define.
- Examples include finding a job or solving a crime; most real-world problems fall into this category.

Examines how problems are represented and what information is considered key.
Gestalt psychologists dismiss trial-and-error methods focused on past animal studies.
Productive vs. Reproductive Thinking:
- Productive thinking involves insights; reproductive thinking relies on known solutions.
Köhler's studies with chimpanzees demonstrated problem-solving through insight ("Eureka" moments).

Surface Features: Irrelevant but noticeable aspects of a problem.
Functional Fixedness: The tendency to stick to usual uses of problem elements, hindering new solutions.
Einstellung: Reliance on known solutions can lead to missing better options.

Solving new problems can be aided by recognizing analogies with others.
Success in analogical transfer depends on:
- Direct comparison of problems.
- Similar content or structural relationships.

Pioneered by Alan Newell and Herb Simon, foundational in cognitive science and AI.
Problem Space: All possible states between initial and goal conditions.
Operators: Actions that transition the current state.
Means-End Analysis: Involves identifying differences between states and finding appropriate actions.

Developed by Newell, Shaw, and Simon in 1959.
A recursive program designed to solve a wide range of problems using means-end analysis.
Requires problem knowledge on available methods and distance to the goal.

Acquiring extensive knowledge and skills in a domain requires years of practice:
- Example domains: Medicine, law, athletics, and music.
Deliberate Practice:
- Not merely about hours spent practicing; focused on skill improvement, feedback, and coaching.

Expertise enhances working memory for specific domains.
- Example: Chess experts show superior memory for positions after short exposure compared to novices.
Chunk Theory: Experts can encode larger units of information in memory.
Template Theory: Related chunks form templates for understanding more complex scenarios.

Expertise influences attention to relevant diagnostic information.
- Example: Doctors and athletes quickly identify key details in their respective fields.

Experts see different similarities in problems compared to novices, leading to more effective solutions.
Expertise, while essential, is complemented by innate cognitive abilities that can impact learning and career success.

Problem Solving: Approaches include Gestalt and Computational.
Expertise: Involves deliberate practice, improved memory, and problem-solving capabilities.
Study findings support the notion that deliberate practice and talent are both factors in achieving expertise.